Trump Has Turned the GOP Into the Party of Eugenics | New Republic
But eugenics, though discredited, has never been abandoned. In fact, the most powerful people in America appear to enthusiastically embrace the idea that humans can be divided into inherently superior and inferior specimens and treated accordingly. “You have to be born lucky,” President Donald Trump told Oprah Winfrey in 1988, “in the sense that you have to have the right genes.” His biographer Michael D’Antonio explained to Frontline that Trump and his family subscribe “to a racehorse theory of human development. They believe that there are superior people and that if you put together the genes of a superior woman and a superior man, you get a superior offspring.”

So does Trump’s chief strategist Steve Bannon, if the reports are to be believed. Sources told The New York Times this November that despite his devout Catholicism, Bannon “occasionally talked about the genetic superiority of some people and once mused about the desirability of limiting the vote to property owners.” Adam Serwer of The Atlantic reported in January that Attorney General Jeff Sessions praised the Immigration Act of 1924 in a 2015 interview with Bannon, which could be an insight into the views of both these immigration hardliners: The act required would-be immigrants to specify whether they’d ever spent time in prison or the “almshouse,” and if their parents had ever been confined to a psychiatric hospital.
eugenics  fascism  class  American-cultural-assumptions 
16 hours ago
The Little Professor: Taking refuge in a COVE?
What's interesting, though, is the site's goal of generating "not-for-profit income to sustain the future development of tools and publication of COVE material."  On the one hand, scholars have been used, I think, to casually dividing online resources into Free (To Me, Anyway) Sites and Either I Need to Win the Lottery or My University Needs Untoward Quantities of Cash Sites (that last may be a trifle exaggerated, but perhaps not by much).  But, as COVE notes, openly-accessible sites aren't free; even a blog like this one requires an influx of cash ($179.40/yr, to be precise), and something far more elaborate, with lots of interactive tools, images, complex e-texts, moderating behind the scenes, &c. requires considerably more in the way of dollar signs.  Hence the evanescence of many sites.  It will be interesting to see how they succeed in producing a self-funding model that avoids becoming, as they say, "avaricious."   
archives  scholarship  academic-culture  publishing 
20 hours ago
[1702.04748] An Improved Dictatorship Test with Perfect Completeness
A Boolean function f:{0,1}n→{0,1} is called a dictator if it depends on exactly one variable i.e f(x1,x2,…,xn)=xi for some i∈[n]. In this work, we study a k-query dictatorship test. Dictatorship tests are central in proving many hardness results for constraint satisfaction problems.
The dictatorship test is said to have {\em perfect completeness} if it accepts any dictator function. The {\em soundness} of a test is the maximum probability with which it accepts any function far from a dictator. Our main result is a k-query dictatorship test with perfect completeness and soundness 2k+12k, where k is of the form 2t−1 for any integer t>2. This improves upon the result of \cite{TY15} which gave a dictatorship test with soundness 2k+32k.
constraint-satisfaction  computational-complexity  rather-interesting  approximation  heuristics  nudge-targets  consider:classification 
You Can’t Break Math – dy/dan

I haven’t found a way to generate these kinds of insights about math without surrounding myself with people learning math for the first time.
One of my most enduring shortcomings as a teacher is how much I plan and revise those plans, even if the lesson I have on file will suffice. I’ll chase a scintilla of an improvement for hours, which was never sustainable. I spent most of the previous day prepping this Desmos activity. We used 10% of it.
Language from the day that I’m still pondering: “We cancel the 2x’s because we want to get x by itself.” I’m trying to decide if those italicized expressions contribute to a student’s understanding of large ideas about mathematics or of small ideas about solving a particular kind of equation.
pedagogy  the-mangle-in-practice  learning-by-doing  looking-to-see  rather-interesting  mathematics  to-write-about 
2 days ago
[1701.00736] Simulated Tornado Optimization
We propose a swarm-based optimization algorithm inspired by air currents of a tornado. Two main air currents - spiral and updraft - are mimicked. Spiral motion is designed for exploration of new search areas and updraft movements is deployed for exploitation of a promising candidate solution. Assignment of just one search direction to each particle at each iteration, leads to low computational complexity of the proposed algorithm respect to the conventional algorithms. Regardless of the step size parameters, the only parameter of the proposed algorithm, called tornado diameter, can be efficiently adjusted by randomization. Numerical results over six different benchmark cost functions indicate comparable and, in some cases, better performance of the proposed algorithm respect to some other metaheuristics.
another-metaheuristic  not-that-bad-actually  metaheuristics  algorithms  swarms  to-write-about  exploration-and-exploitation 
2 days ago
Waclaw Szpakowski Made Labyrinthine Drawings from Single, Continuous Lines
Working in isolation, Wacław Szpakowski made mazelike drawings from single, continuous lines.
art  abstraction  geometry  self-similarity  history  nanohistory 
2 days ago
The Archdruid Report: Perched on the Wheel of Time
In the final chapters of his second volume, for example, Spengler noted that civilizations in the stage ours was about to reach always end up racked by conflicts that pit established hierarchies against upstart demagogues who rally the disaffected and transform them into a power base. Looking at the trends visible in his own time, he sketched out the most likely form those conflicts would take in the Winter phase of our civilization. Modern representative democracy, he pointed out, has no effective defenses against corruption by wealth, and so could be expected to evolve into corporate-bureaucratic plutocracies that benefit the affluent at the expense of everyone else. Those left out in the cold by these transformations, in turn, end up backing what Spengler called Caesarism—the rise of charismatic demagogues who challenge and eventually overturn the corporate-bureaucratic order.

These demagogues needn’t come from within the excluded classes, by the way. Julius Caesar, the obvious example, came from an old upper-class Roman family and parlayed his family connections into a successful political career. Watchers of the current political scene may be interested to know that Caesar during his lifetime wasn’t the imposing figure he became in retrospect; he had a high shrill voice, his morals were remarkably flexible even by Roman standards—the scurrilous gossip of his time called him “every man’s wife and every woman’s husband”—and he spent much of his career piling up huge debts and then wriggling out from under them. Yet he became the political standardbearer for the plebeian classes, and his assassination by a conspiracy of rich Senators launched the era of civil wars that ended the rule of the old elite once and for all.
history  political-economy  philosophy  models-and-modes  argumentation 
2 days ago
The Archdruid Report: The World as Representation
Doing that, though, would require an attitude we might as well call epistemic modesty: the recognition that the human capacity to know has hard limits, and the unqualified absolute truth about most things is out of our reach. Socrates was called the wisest of the Greeks because he accepted the need for epistemic modesty, and recognized that he didn’t actually know much of anything for certain. That recognition didn’t keep him from being able to get up in the morning and go to work at his day job as a stonecutter, and it needn’t keep the rest of us from doing what we have to do as industrial civilization lurches down the trajectory toward a difficult future.

Taken seriously, though, epistemic modesty requires some serious second thoughts about certain very deeply ingrained presuppositions of the cultures of the West. Some of those second thoughts are fairly easy to reach, but one of the most challenging starts with a seemingly simple question: is there anything we experience that isn’t a representation? In the weeks ahead we’ll track that question all the way to its deeply troubling destination.
philosophy-of-science  philosophy  cultural-assumptions  scientism  rather-interesting  to-write-about 
2 days ago
Microsoft shares open source system for training drones, other gadgets to move safely on their own - Next at Microsoft
Let’s say you want to teach an aerial robot to tell the difference between a wall and a shadow. Chances are, you’d like to test your theories without crashing hundreds of drones into walls.

Until recently, simulators provided some help for this kind of testing, but they weren’t accurate enough to truly reflect the complexities of the real world. That’s key to developing systems that can accurately perceive the world around them in the same way that people do.

Now, thanks to big advances in graphics hardware, computing power and algorithms, Microsoft researchers say they can create simulators that offer a much more realistic view of the environment. Aerial Informatics and Robotics Platform’s simulator is built on the latest photorealistic technologies, which can accurately render subtle things, like shadows and reflections, that make a significant difference in computer vision algorithms.
simulation  virtual-reality  drones  open-source  photorealism  rather-interesting  to-understand  engineering-design 
2 days ago
Variability in fitness effects and the limitations of lineage selection | bioRxiv
Natural selection is sensitive not only to the effect of a trait on total number of offspring produced but also to how a trait affects an individual's entire lineage of descendants. Here we show how a large number of seemingly disparate evolutionary problems, including sex, evolvability, and cooperation, all share the property that fitness varies among members of a lineage. This feature makes it difficult to summarize the evolutionary fate of an allele based solely on its effects on individual reproduction. We show that attempts to average over this variability are often justified, but can sometimes cause misleading results. We then describe a number of intriguing new evolutionary phenomena that have emerged in studies that explicitly model the fate of alleles that influence long-term lineage dynamics. We conclude with prospects for generalizations of population genetics theory and discuss how this theory might be applied to the evolution of infectious diseases.
population-biology  evolutionary-biology  agent-based  fitness  define-your-terms  rather-interesting  to-write-about  consider:effects-in-GAs 
2 days ago
[1702.00020] Towards "AlphaChem": Chemical Synthesis Planning with Tree Search and Deep Neural Network Policies
Retrosynthesis is a technique to plan the chemical synthesis of organic molecules, for example drugs, agro- and fine chemicals. In retrosynthesis, a search tree is built by analysing molecules recursively and dissecting them into simpler molecular building blocks until one obtains a set of known building blocks. The search space is intractably large, and it is difficult to determine the value of retrosynthetic positions. Here, we propose to model retrosynthesis as a Markov Decision Process. In combination with a Deep Neural Network policy learned from essentially the complete published knowledge of chemistry, Monte Carlo Tree Search (MCTS) can be used to evaluate positions. In exploratory studies, we demonstrate that MCTS with neural network policies outperforms the traditionally used best-first search with hand-coded heuristics.
engineering-design  deep-learning  neural-networks  planning  cheminformatics  nudge-targets  consider:looking-to-see 
2 days ago
[1701.00419] The tilings of deficient squares by ribbon L-tetrominoes are diagonally cracked
We consider tilings of deficient rectangles by the set 4 of ribbon L-tetrominoes. A tiling exists iff the rectangle is a square of odd side. The missing cell is on the main NW--SE diagonal, in an odd position if the square is (4m+1)×(4m+1) and in an even position for (4m+3)×(4m+3). The majority of the tiles in a tiling are paired and each pair tiles a 2×4 rectangle. The tiles in an irregular position and the missing cell form a NW--SE diagonal crack, located in a thin region symmetric about the diagonal, made out of 3×3 squares that overlap over one of the corner cells. The crack divides the square in two equal area parts. The number of tilings of a (4m+1)×(4m+1) deficient square is equal to the number of tilings by dominoes of a 2m×2m square. The number of tilings of a (4m+3)×(4m+3) deficient square is twice the number of tilings by dominoes of a (2m+1)×(2m+1) deficient square, with missing cell placed on the main diagonal. If an extra 2×2 tile is added to 4, we call the new tile set +4. A tiling of a deficient rectangle by +4 exists iff the rectangle is a square of odd side. The missing cell is on the main NW--SE diagonal, in an odd position if the square is (4m+1)×(4m+1) and in an even position for (4m+3)×(4m+3). The majority of the tiles in a tiling are either paired tetrominoes and each pair tiles a 2×4 rectangle, or are 2×2 squares. The tiles in an irregular position and the missing cell form a NW--SE diagonal crack, located in a thin region symmetric about the diagonal, made out of 3×3 squares that overlap over one of the corner cells.
tiling  proof  rather-interesting  nudge-targets  consider:looking-to-see  consider:how-far-can-it-go  consider:feature-discovery  mathematical-recreations 
2 days ago
[1309.3267] The Apollonian structure of integer superharmonic matrices
We prove that the set of quadratic growths attainable by integer-valued superharmonic functions on the lattice ℤ2 has the structure of an Apollonian circle packing. This completely characterizes the PDE which determines the continuum scaling limit of the Abelian sandpile on the lattice ℤ2.
to-understand  purdy-pitchers  mathematics  connections 
2 days ago
[1701.01337] Abilities and Limitations of Spectral Graph Bisection
Spectral based heuristics belong to well-known commonly used methods for finding a minimum-size bisection in a graph. The heuristics are usually easy to implement and they work well for several practice-relevant classes of graphs. However, only a few research efforts are focused on providing rigorous analysis of such heuristics and often they lack of proven optimality or approximation quality. This paper focuses on the spectral heuristic proposed by Boppana almost three decades ago, which still belongs to one of the most important bisection methods.
It is well known that Boppana's algorithm finds and certifies an optimal bisection with high probability in the random planted bisection model -- the standard model which captures many real-world instances. In this model the vertex set is partitioned randomly into two equal sized sets, and then each edge inside the same part of the partition is chosen with probability p and each edge crossing the partition is chosen with probability q, with p≥q. In our paper we investigate the problem if Boppana's algorithm works well in the semirandom model introduced by Feige and Kilian. The model generates initially an instance by random selection within the planted bisection model, followed by adversarial decisions. Feige and Kilian posed the question if Boppana's algorithm works well in the semirandom model and it has remained open so far. In our paper we answer the question affirmatively. We show also that the algorithm achieves similar performance on graph models which generalize the semirandom model. On the other hand we prove some limitations: we show that if the density difference p−q≤o(p⋅lnn‾‾‾‾‾‾√/n‾√) then the algorithm fails with high probability in the planted bisection model. This bound is sharp, since under assumption p−q≥Ω(p⋅lnn‾‾‾‾‾‾√/n‾√) Boppana's algorithm works well in the model.
graph-theory  algorithms  bisection  horse-races  approximation  nudge-targets  consider:representation 
2 days ago
[1701.09046] An Extremal Optimization approach to parallel resonance constrained capacitor placement problem
Installation of capacitors in distribution networks is one of the most used procedure to compensate reactive power generated by loads and, consequently, to reduce technical losses. So, the problem consists in identifying the optimal placement and sizing of capacitors. This problem is known in the literature as optimal capacitor placement problem. Neverthless, depending on the location and size of the capacitor, it may become a harmonic source, allowing capacitor to enter into resonance with the distribution network, causing several undesired side effects. In this work we propose a parsimonious method to deal with the capacitor placement problem that incorporates resonance constraints, ensuring that every allocated capacitor will not act as a harmonic source. This proposed algorithm is based upon a physical inspired metaheuristic known as Extremal Optimization. The results achieved showed that this proposal has reached significant gains when compared with other proposals that attempt repair, in a post-optimization stage, already obtained solutions which violate resonance constraints.
engineering-design  complex-systems  operations-research  multiobjective-optimization  robustness  electromagnetism  to-write-about  rather-interesting  optimization  nudge-targets  consider:feature-discovery 
2 days ago
[1702.01446] Efficient Algorithms for k-Regret Minimizing Sets
A regret minimizing set Q is a small size representation of a much larger database P so that user queries executed on Q return answers whose scores are not much worse than those on the full dataset. In particular, a k-regret minimizing set has the property that the regret ratio between the score of the top-1 item in Q and the score of the top-k item in P is minimized, where the score of an item is the inner product of the item's attributes with a user's weight (preference) vector. The problem is challenging because we want to find a single representative set Q whose regret ratio is small with respect to all possible user weight vectors.
We show that k-regret minimization is NP-Complete for all dimensions d >= 3. This settles an open problem from Chester et al. [VLDB 2014], and resolves the complexity status of the problem for all d: the problem is known to have polynomial-time solution for d <= 2. In addition, we propose two new approximation schemes for regret minimization, both with provable guarantees, one based on coresets and another based on hitting sets. We also carry out extensive experimental evaluation, and show that our schemes compute regret-minimizing sets comparable in size to the greedy algorithm proposed in [VLDB 14] but our schemes are significantly faster and scalable to large data sets.
databases  multiobjective-optimization  rather-interesting  algorithms  computational-complexity  to-write-about  benchmarking  consider:looking-to-see  consider:skylines 
2 days ago
[1608.02014] Assessing significance in a Markov chain without mixing
We present a new statistical test to detect that a presented state of a reversible Markov chain was not chosen from a stationary distribution. In particular, given a value function for the states of the Markov chain, we would like to demonstrate rigorously that the presented state is an outlier with respect to the values, by establishing a p-value for observations we make about the state under the null hypothesis that it was chosen uniformly at random.
A simple heuristic used in practice is to sample ranks of states from long random trajectories on the Markov chain, and compare these to the rank of the presented state; if the presented state is a 0.1%-outlier compared to the sampled ranks (i.e., its rank is in the bottom 0.1% of sampled ranks) then this should correspond to a p-value of 0.001. This test is not rigorous, however, without good bounds on the mixing time of the Markov chain, as one must argue that the observed states on the trajectory approximate the stationary distribution.
Our test is the following: given the presented state in the Markov chain, take a random walk from the presented state for any number of steps. We prove that observing that the presented state is an ε-outlier on the walk is significant at p=2ε‾‾√, under the null hypothesis that the state was chosen from a stationary distribution. Our result assumes nothing about the structure of the Markov chain beyond reversibility, and we construct examples to show that significance at p≈ε√ is essentially best possible in general. We illustrate the use of our test with a potential application to the rigorous detection of gerrymandering in Congressional districtings.
statistics  Markov-chains  random-walks  stochastic-systems  rather-interesting  statistical-test  algorithms  to-write-about  politics  redistricting  fairness 
2 days ago
[1701.00833] Fuzzy finite element model updating using metaheuristic optimization algorithms
In this paper, a non-probabilistic method based on fuzzy logic is used to update finite element models (FEMs). Model updating techniques use the measured data to improve the accuracy of numerical models of structures. However, the measured data are contaminated with experimental noise and the models are inaccurate due to randomness in the parameters. This kind of aleatory uncertainty is irreducible, and may decrease the accuracy of the finite element model updating process. However, uncertainty quantification methods can be used to identify the uncertainty in the updating parameters. In this paper, the uncertainties associated with the modal parameters are defined as fuzzy membership functions, while the model updating procedure is defined as an optimization problem at each {\alpha}-cut level. To determine the membership functions of the updated parameters, an objective function is defined and minimized using two metaheuristic optimization algorithms: ant colony optimization (ACO) and particle swarm optimization (PSO). A structural example is used to investigate the accuracy of the fuzzy model updating strategy using the PSO and ACO algorithms. Furthermore, the results obtained by the fuzzy finite element model updating are compared with the Bayesian model updating results.
metaheuristics  fuzzy-numbers  rather-interesting  representation  optimization  nudge-targets  consider:representation  consider:looking-to-see  to-write-about 
2 days ago
Love Trumps Hate? Liberalism's False Opposition to Trump - IT'S GOING DOWN
Love and hate are emotions that cannot appropriately be assigned to systems of power. The real problem is structural. It is the police, the law, political parties, and capitalism. It is 500 years of colonialism and anti-blackness and rape culture. None of what Trump is trying to do would be possible if these systems did not exist. What matters about Obama’s deportation of 2.4 million people is not his personal feelings for those folks. What matters is that he deported over 2.4 million people. Put another way, the boss does not exploit his workers because he hates them—he does so because his position in the economy demands it. Individual cops do not occupy and harass black neighborhoods out of personal spite (even if many enjoy it)—they do so because if they were to refuse, they would simply be fired and replaced. Power, freedom, and survival are what is at stake here, not just feelings.
structural-problems  systemic-evil  politics  sociology  American-cultural-assumptions 
3 days ago
Days of Rage | Status 451
Everything goes smoothly in Weather’s plan until the PFOC conference happens, which looks stunningly like what we’re seeing emerge in today’s Democratic party politics. The white leftist elites (Weather) are stunned to discover that the diverse radicals (black, American Indian, Puerto Rican) they’ve imagined leading actually have opinions of their own, and perfectly rational desires for their own power, and no desire to be ruled by Weather’s upper-crust radicals.

One of Burrough’s Weather interviewees notes that she was very upset and rattled to continually be called racist. This was before white leftists started to unpack their invisible knapsacks and bewail their whiteness as original sin. She couldn’t grasp it.

In the end, Weather was ignominously expelled from their own conference by a Communist who had been one of their former members. (Said Commie later got arrested himself by the Feds when he tried to start a bombing campaign of his own).
history  American-cultural-assumptions  politics  social-dynamics 
4 days ago
[1702.02891] Sparse Approximation by Semidefinite Programming
The problem of sparse approximation and the closely related compressed sensing have received tremendous attention in the past decade. Primarily studied from the viewpoint of applied harmonic analysis and signal processing, there have been two dominant algorithmic approaches to this problem: Greedy methods called the matching pursuit (MP) and the linear programming based approaches called the basis pursuit (BP). The aim of the current paper is to bring a fresh perspective to sparse approximation by treating it as a combinatorial optimization problem and providing an algorithm based on the powerful optimization technique semidefinite programming (SDP). In particular, we show that there is a randomized algorithm based on a semidefinite relaxation of the problem with performance guarantees depending on the coherence and the restricted isometry constant of the dictionary used. We then show a derandomization of the algorithm based on the method of conditional probabilities.
approximation  compressed-sensing  representation  mathematical-programming  numerical-methods  performance-measure  nudge-targets  consider:looking-to-see  consider:feature-discovery 
4 days ago
Inside an AI 'brain' - What does machine learning look like?
One aspect all recent machine learning frameworks have in common - TensorFlow, MxNet, Caffe, Theano, Torch and others - is that they use the concept of a computational graph as a powerful abstraction. A graph is simply the best way to describe the models you create in a machine learning system. These computational graphs are made up of vertices (think neurons) for the compute elements, connected by edges (think synapses), which describe the communication paths between vertices.
visualization  very-nice  to-write-about  graph-theory  deep-learning 
5 days ago
Machine with Roller Chain - Arthur Ganson - YouTube
A simple exploration of the organic nature and complexity of roller chain. The shapes and patterns most likely will never repeat. Often, heavy industrial materials have a 'softer side' that is not revealed if they are used only as intended.
conceptual-art  mechanics  engineering-design  art  video 
5 days ago
Machine with Concrete - Arthur Ganson - YouTube
This machine was inspired by dreaming about gear ratios and considering the unexpected implications of exponential powers.

Each worm/worm gear pair reduces the speed of the motor by 1/50th. Since there are 12 pairs of gears, the final speed reduction is calculated by (1/50)12. The implications are quite large. With the motor turning around 200 revolutions per minute, it will take well over two trillion years before the final gear makes but one turn. Given the truth of this situation, it is possible to do anything at all with the final gear, even embed it in concrete.
conceptual-art  video  engineering-design  amusing  via:ronjeffries  mechanics 
5 days ago
[1702.02939] cellGPU: massively parallel simulations of dynamic vertex models
Vertex models represent confluent tissue by polygonal or polyhedral tilings of space, with the individual cell interacting via force laws that depend on both the geometry of the cells and the topology of the tessellation. This dependence on the connectivity of the cellular network introduces several complications to performing molecular-dynamics-like simulations of vertex models, and in particular makes parallelizing the simulations difficult. cellGPU addresses this difficulty and lays the foundation for massively parallelized, GPU-based simulations of these models. This article discusses its implementation for a pair of two-dimensional models, and compares the typical performance that can be expected between running cellGPU entirely on the CPU versus its performance when running on a range of commercial and server-grade graphics cards. By implementing the calculation of topological changes and forces on cells in a highly parallelizable fashion, cellGPU enables researchers to simulate time- and length-scales previously inaccessible via existing single-threaded CPU implementations.
tiling  computational-geometry  GPU  algorithms  rather-interesting  horse-races  computational-complexity 
5 days ago
[1702.02823] Artificial Intelligence as an Enabler for Cognitive Self-Organizing Future Networks
The explosive increase in number of smart devices hosting sophisticated applications is rapidly affecting the landscape of information communication technology industry. Mobile subscriptions, expected to reach 8.9 billion by 2022, would drastically increase the demand of extra capacity with aggregate throughput anticipated to be enhanced by a factor of 1000. In an already crowded radio spectrum, it becomes increasingly difficult to meet ever growing application demands of wireless bandwidth. It has been shown that the allocated spectrum is seldom utilized by the primary users and hence contains spectrum holes that may be exploited by the unlicensed users for their communication. As we enter the Internet Of Things (IoT) era in which appliances of common use will become smart digital devices with rigid performance requirements (such as low latency, energy efficiency, etc.), current networks face the vexing problem of how to create sufficient capacity for such applications. The fifth generation of cellular networks (5G) envisioned to address these challenges are thus required to incorporate cognition and intelligence to resolve the aforementioned issues.
cognitive-radio  machine-learning  collective-behavior  self-organization  radio  engineering-design 
5 days ago
[1702.02808] Memetic search for overlapping topics based on a local evaluation of link communities
In spite of recent advances in field delineation methods, bibliometricians still don't know the extent to which their topic detection algorithms reconstruct `ground truths', i.e. thematic structures in the scientific literature. In this paper, we demonstrate a new approach to the delineation of thematic structures that attempts to match the algorithm to theoretically derived and empirically observed properties all thematic structures have in common. We cluster citation links rather than publication nodes, use predominantly local information and search for communities of links starting from seed subgraphs in order to allow for pervasive overlaps of topics. We evaluate sets of links with a new cost function and assume that local minima in the cost landscape correspond to link communities. Because this cost landscape has many local minima we define a valid community as the community with the lowest minimum within a certain range. Since finding all valid communities is impossible for large networks, we designed a memetic algorithm that combines probabilistic evolutionary strategies with deterministic local searches. We apply our approach to a network of about 15,000 Astronomy & Astrophysics papers published 2010 and their cited sources, and to a network of about 100,000 Astronomy & Astrophysics papers (published 2003--2010) which are linked through direct citations.
bibliometrics  citation  social-networks  feature-extraction  clustering  rather-interesting  academic-culture  system-of-professions 
5 days ago
[1701.09175] Skip Connections as Effective Symmetry-Breaking
Skip connections made the training of very deep neural networks possible and have become an indispendable component in a variety of neural architectures. A completely satisfactory explanation for their success remains elusive. Here, we present a novel explanation for the benefits of skip connections in training very deep neural networks. We argue that skip connections help break symmetries inherent in the loss landscapes of deep networks, leading to drastically simplified landscapes. In particular, skip connections between adjacent layers in a multilayer network break the permutation symmetry of nodes in a given layer, and the recently proposed DenseNet architecture, where each layer projects skip connections to every layer above it, also breaks the rescaling symmetry of connectivity matrices between different layers. This hypothesis is supported by evidence from a toy model with binary weights and from experiments with fully-connected networks suggesting (i) that skip connections do not necessarily improve training unless they help break symmetries and (ii) that alternative ways of breaking the symmetries also lead to significant performance improvements in training deep networks, hence there is nothing special about skip connections in this respect. We find, however, that skip connections confer additional benefits over and above symmetry-breaking, such as the ability to deal effectively with the vanishing gradients problem.
neural-networks  learning  fitness-landscapes  engineering-design  rather-interesting  symmetry  nudge-targets  consider:looking-to-see 
5 days ago
Tanya Khovanova's Math Blog » Blog Archive » Alternators: People and Coins
So we have 11 coins, one of which is an alternator. In the first weighing we compare 5 coins against 5 coins. If the weighing unbalances, the alternator is on a lighter pan. Our problem is reduced to finding the alternator among five coins when we know that it is in the real state. If the weighing balances, then we know that if the alternator is among the coins on the scale it must now be in the light state. For the second weighting, we pick two sets of three coins out of this ten coins and compare them against each other. Notice that 3 is a Jacobsthal number, and 5, the number of coins outside the scale, is also a Jacobsthal number. If the second weighing balances, the alternator must be among 5 coins outside the scale. All but one of these coins are in the light state, and I leave it to the readers to finish the strategy. If the weighing unbalances, we need to find the alternator among 3 coins that are in the real state now. This can be done in two weighings, and again the readers are to the rescue.
mathematical-recreations  nudge-targets  consider:looking-to-see 
5 days ago
Negations: Capitalism and Schizophrenia
This article demonstrates the psychological link between one-dimensionality and advertising.
6 days ago
numbness | The Chicago School of Media Theory
The modern person is daily inundated with a flood of media news coverage, television commercials, billboards, and advertisements. Media is everywhere and unavoidable. Urbanites can hardly step outside their door without being bombarded with a plethora of media stimuli. In spite of this, however, millions of people are not being rushed to emergency rooms as a result of this deluge of stimuli. Instead, there is an anesthetic effect, a numbness that has dulled the senses from noticing each and every stimulus.
6 days ago
Serverless Architectures
Serverless architectures refer to applications that significantly depend on third-party services (knows as Backend as a Service or "BaaS") or on custom code that's run in ephemeral containers (Function as a Service or "FaaS"), the best known vendor host of which currently is AWS Lambda. By using these ideas, and by moving much behavior to the front end, such architectures remove the need for the traditional 'always on' server system sitting behind an application. Depending on the circumstances, such systems can significantly reduce operational cost and complexity at a cost of vendor dependencies and (at the moment) immaturity of supporting services.
serverless  architecture  software-development  software-development-is-not-programming  cloud-computing 
6 days ago
[1402.4914] Building fast Bayesian computing machines out of intentionally stochastic, digital parts
The brain interprets ambiguous sensory information faster and more reliably than modern computers, using neurons that are slower and less reliable than logic gates. But Bayesian inference, which underpins many computational models of perception and cognition, appears computationally challenging even given modern transistor speeds and energy budgets. The computational principles and structures needed to narrow this gap are unknown. Here we show how to build fast Bayesian computing machines using intentionally stochastic, digital parts, narrowing this efficiency gap by multiple orders of magnitude. We find that by connecting stochastic digital components according to simple mathematical rules, one can build massively parallel, low precision circuits that solve Bayesian inference problems and are compatible with the Poisson firing statistics of cortical neurons. We evaluate circuits for depth and motion perception, perceptual learning and causal reasoning, each performing inference over 10,000+ latent variables in real time - a 1,000x speed advantage over commodity microprocessors. These results suggest a new role for randomness in the engineering and reverse-engineering of intelligent computation.
via:shafto  to-read  rather-interesting  representation  nonlinear-dynamics  engineering-design  stochastic-systems  nudge-targets  consider:looking-to-see  consider:artificial-chemistries 
7 days ago
Death of an order: a comprehensive molecular phylogenetic study confirms that termites are eusocial cockroaches | Biology Letters
Termites are instantly recognizable mound-builders and house-eaters: their complex social lifestyles have made them incredibly successful throughout the tropics. Although known as ‘white ants’, they are not ants and their relationships with other insects remain unclear. Our molecular phylogenetic analyses, the most comprehensive yet attempted, show that termites are social cockroaches, no longer meriting being classified as a separate order (Isoptera) from the cockroaches (Blattodea). Instead, we propose that they should be treated as a family (Termitidae) of cockroaches. It is surprising to find that a group of wood-feeding cockroaches has evolved full sociality, as other ecologically dominant fully social insects (e.g. ants, social bees and social wasps) have evolved from solitary predatory wasps.
via:arthegall  evolutionary-biology  cladistics  entomology  rather-interesting  naming-is-hard 
7 days ago
5th grade charter school teacher Mika Yamamoto, fired from Michigan’s Renaissance Public School Academy, where she was the only teacher of color, claims she was told by her principal, “The community is not ready for your voice.”
5th grade charter school teacher Mika Yamamoto, fired from Michigan’s Renaissance Public School Academy, where she was the only teacher of color, claims she was told by her principal, “The community is not ready for your voice.”
local  via:twitter  fascism 
7 days ago
Anonymous infiltrated the KKK by friending Blue Lives Matter supporters on Facebook / Boing Boing
The Anonymous activists behind "OpKKK" -- which infiltrated and unmasked Klan members, including many in US military and police departments -- began by creating thin-but-plausible fake identities on Facebook that signalled support for "Blue Lives Matter." By friending other accounts that indicated support for Blue Lives Matter, they found themselves being auto-suggested friendships with KKK members.
fascism  via:twitter 
8 days ago
[1607.00318] The Evolution of Sex through the Baldwin Effect
This paper suggests that the fundamental haploid-diploid cycle of eukaryotic sex exploits a rudimentary form of the Baldwin effect. With this explanation for the basic cycle, the other associated phenomena can be explained as evolution tuning the amount and frequency of learning experienced by an organism. Using the well-known NK model of fitness landscapes it is shown that varying landscape ruggedness varies the benefit of the haploid-diploid cycle, whether based upon endomitosis or syngamy. The utility of mechanisms such as pre-meiotic doubling and recombination during the cycle are also shown to vary with landscape ruggedness. This view is suggested as underpinning, rather than contradicting, many existing explanations for sex.
Kauffmania  fitness-landscapes  theoretical-biology  questionable-graphs  to-write-about 
8 days ago
[1702.02821] Phase Transitions of the Typical Algorithmic Complexity of the Random Satisfiability Problem Studied with Linear Programming
The Boolean Satisfiability problem asks if a Boolean formula is satisfiable by some assignment of the variables or not. It belongs to the NP-complete complexity class and hence no algorithm with polynomial time worst-case complexity is known, i.e., the problem is hard. The K-SAT problem is the subset of the Boolean Satisfiability problem, for which the Boolean formula has the conjunctive normal form with K literals per clause. This problem is still NP-complete for K≥3. Although the worst case complexity of NP-complete problems is conjectured to be exponential, there might be subsets of the realizations where solutions can typically be found in polynomial time. In fact, random K-SAT, with the number of clauses to number of variables ratio α as control parameter, shows a phase transition between a satisfiable phase and an unsatisfiable phase, at which the hardest problems are located. We use here several linear programming approaches to reveal further "easy-hard" transition points at which the typical hardness of the problems increases which means that such algorithms can solve the problem on one side efficiently but not beyond this point. For one of these transitions, we observed a coincidence with a structural transition of the literal factor graphs of the problem instances. We also investigated cutting-plane approaches, which often increase the computational efficiency. Also we tried out a mapping to another NP-complete optimization problem using a specific algorithm for that problem. In both cases, no improvement of the performance was observed, i.e., no shift of the easy-hard transition to higher values of α.
phase-transitions  satisfiability  rather-interesting  nudge-targets  consider:feature-discovery  consider:classification 
8 days ago
The future of scholarly publishing – Green Tea and Velociraptors
If we were to have to invent the scholarly publishing system again from scratch today, what would it look like?

Our current system of publishing is basically identical to that of what it was in the 1990s, before the emergence of a vast array of internet-based technologies, loosely termed Web 2.0. A research paper is a 20th century format, published in a 17th century container – the journal.

Ironically, this system still persists despite the blatant fact that anyone can publish anything they want at the touch of a button these days. Yet scholarly publishing still usually takes months, and some times takes even years, just to upload content to the Web.
via:twitter  scholarship  academic-culture  public-policy  open-access 
8 days ago
The Spy Revolt Against Donald Trump Begins | Observer
Now those concerns are causing problems much closer to home—in fact, inside the Beltway itself. Our Intelligence Community is so worried by the unprecedented problems of the Trump administration—not only do senior officials possess troubling ties to the Kremlin, there are nagging questions about basic competence regarding Team Trump—that it is beginning to withhold intelligence from a White House which our spies do not trust.

That the IC has ample grounds for concern is demonstrated by almost daily revelations of major problems inside the White House, a mere three weeks after the inauguration. The president has repeatedly gone out of his way to antagonize our spies, mocking them and demeaning their work, and Trump’s personal national security guru can’t seem to keep his story straight on vital issues.
That’s Mike Flynn, the retired Army three-star general who now heads the National Security Council. Widely disliked in Washington for his brash personality and preference for conspiracy-theorizing over intelligence facts, Flynn was fired as head of the Defense Intelligence Agency for managerial incompetence and poor judgment—flaws he has brought to the far more powerful and political NSC.

Flynn’s problems with the truth have been laid bare by the growing scandal about his dealings with Moscow. Strange ties to the Kremlin, including Vladimir Putin himself, have dogged Flynn since he left DIA, and concerns about his judgment have risen considerably since it was revealed that after the November 8 election, Flynn repeatedly called the Russian embassy in Washington to discuss the transition. The White House has denied that anything substantive came up in conversations between Flynn and Sergei Kislyak, the Russian ambassador.
9 days ago
eli neiburger on Twitter:
At UM Euph & Tuba ensemble concert. Composer introducing his world-premiere piece: "I don't know how many of you have heard of Cthulhu..."
9 days ago
When invisible noise obscures the signal: the consequences of nonlinearity in motion detection | bioRxiv
The motion energy model is the standard account of motion detection in animals from beetles to humans. Despite this common basis, we show here that a difference in the early stages of visual processing between mammals and insects leads this model to make radically different behavioural predictions. In insects, early filtering is spatially lowpass, which makes the surprising prediction that motion detection can be impaired by “invisible” noise, i.e. noise at a spatial frequency that elicits no response when presented on its own as a signal. We confirm this prediction using the optomotor response of praying mantis Sphodromantis lineola. This does not occur in mammals, where spatially bandpass early filtering means that linear systems techniques, such as deriving channel sensitivity from masking functions, remain approximately valid. Counter-intuitive effects such as masking by invisible noise may occur in neural circuits wherever a nonlinearity is followed by a difference operation.
rather-interesting  signal-processing  biology  neural-networks  nudge-targets  consider:looking-to-see  consider:evolving-architectures 
9 days ago
[1604.04722] Where is the global corporate elite? A large-scale network study of local and nonlocal interlocking directorates
Business elites reconfigure their locus of organization over time, from the city level, to the national level, and beyond. We ask what the current level of elite organization is and propose a novel theoretical and empirical approach to answer this question. Building on the universal distinction between local and nonlocal ties we use network analysis and community detection to dissect the global network of interlocking directorates among over five million firms. We find that elite orientation is indeed changing from the national to the transnational plane, but we register a considerable heterogeneity across different regions in the world. In some regions the business communities are organized along national borders, whereas in other areas the locus of organization is at the city level or international level. London dominates the global corporate elite network. Our findings underscore that the study of corporate elites requires an approach that is sensitive to levels of organization that go beyond the confines of nation states.
social-networks  rather-interesting  corporatism  globalism  looking-to-see  to-write-about 
9 days ago
[1610.01674] Who is Who in Phylogenetic Networks: Articles, Authors and Programs
The phylogenetic network emerged in the 1990s as a new model to represent the evolution of species in the case where coexisting species transfer genetic information through hybridization, recombination, lateral gene transfer, etc. As is true for many rapidly evolving fields, there is considerable fragmentation and diversity in methodologies, standards and vocabulary in phylogenetic network research, thus creating the need for an integrated database of articles, authors, techniques, keywords and software. We describe such a database, "Who is Who in Phylogenetic Networks", available at this http URL "Who is Who in Phylogenetic Networks" comprises more than 600 publications and 500 authors interlinked with a rich set of more than 200 keywords related to phylogenetic networks. The database is integrated with web-based tools to visualize authorship and collaboration networks and analyze these networks using common graph and social network metrics such as centrality (betweenness, eigenvector, degree and closeness) and clustering. We provide downloads of raw information about entries in the database, and a facility to suggest modifications and contribute new information to the database. We also present in this article common use cases of the database and identify trends in the research on phylogenetic networks using the information in the database and textual analysis.
phylogenetics  rather-interesting  network-theory  review  evolutionary-biology  representation  bibliography 
9 days ago
[1604.04660] Why Artificial Intelligence Needs a Task Theory --- And What It Might Look Like
The concept of "task" is at the core of artificial intelligence (AI): Tasks are used for training and evaluating AI systems, which are built in order to perform and automatize tasks we deem useful. In other fields of engineering theoretical foundations allow thorough evaluation of designs by methodical manipulation of well understood parameters with a known role and importance; this allows an aeronautics engineer, for instance, to systematically assess the effects of wind speed on an airplane's performance and stability. No framework exists in AI that allows this kind of methodical manipulation: Performance results on the few tasks in current use (cf. board games, question-answering) cannot be easily compared, however similar or different. The issue is even more acute with respect to artificial *general* intelligence systems, which must handle unanticipated tasks whose specifics cannot be known beforehand. A *task theory* would enable addressing tasks at the *class* level, bypassing their specifics, providing the appropriate formalization and classification of tasks, environments, and their parameters, resulting in more rigorous ways of measuring, comparing, and evaluating intelligent behavior. Even modest improvements in this direction would surpass the current ad-hoc nature of machine learning and AI evaluation. Here we discuss the main elements of the argument for a task theory and present an outline of what it might look like for physical tasks.
artificial-intelligence  philosophy-of-engineering  rather-interesting  representation  approximation  aggregation  nudge-targets  consider:looking-to-see  consider:performance-space-analysis 
9 days ago
[1702.00030] The optimisation of low-acceleration interstellar relativistic rocket trajectories using genetic algorithms
A vast wealth of literature exists on the topic of rocket trajectory optimisation, particularly in the area of interplanetary trajectories due to its relevance today. Studies on optimising interstellar and intergalactic trajectories are usually performed in flat spacetime using an analytical approach, with very little focus on optimising interstellar trajectories in a general relativistic framework. This paper examines the use of low-acceleration rockets to reach galactic destinations in the least possible time, with a genetic algorithm being employed for the optimisation process. The fuel required for each journey was calculated for various types of propulsion systems to determine the viability of low-acceleration rockets to colonise the Milky Way. The results showed that to limit the amount of fuel carried on board, an antimatter propulsion system would likely be the minimum technological requirement to reach star systems tens of thousands of light years away. However, using a low-acceleration rocket would require several hundreds of thousands of years to reach these star systems, with minimal time dilation effects since maximum velocities only reached about 0.2c. Such transit times are clearly impractical, and thus, any kind of colonisation using low acceleration rockets would be difficult. High accelerations, on the order of 1g, are likely required to complete interstellar journeys within a reasonable time frame, though they may require prohibitively large amounts of fuel. So for now, it appears that humanity's ultimate goal of a galactic empire may only be possible at significantly higher accelerations, though the propulsion technology requirement for a journey that uses realistic amounts of fuel remains to be determined.
genetic-algorithm  planning  multiobjective-optimization  rather-interesting  to-write-about  nudge-targets  consider:looking-to-see 
9 days ago
[1610.08815] A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks
Sarcasm detection is a key task for many natural language processing tasks. In sentiment analysis, for example, sarcasm can flip the polarity of an "apparently positive" sentence and, hence, negatively affect polarity detection performance. To date, most approaches to sarcasm detection have treated the task primarily as a text categorization problem. Sarcasm, however, can be expressed in very subtle ways and requires a deeper understanding of natural language that standard text categorization techniques cannot grasp. In this work, we develop models based on a pre-trained convolutional neural network for extracting sentiment, emotion and personality features for sarcasm detection. Such features, along with the network's baseline features, allow the proposed models to outperform the state of the art on benchmark datasets. We also address the often ignored generalizability issue of classifying data that have not been seen by the models at learning phase.
machine-learning  natural-language-processing  sentiment-analysis  rather-interesting  feature-construction  nudge-targets  consider:feature-discovery 
9 days ago
[1607.06140] A Haar Wavelet-Based Perceptual Similarity Index for Image Quality Assessment
In most practical situations, images and videos can neither be compressed nor transmitted without introducing distortions that will eventually be perceived by a human observer. Vice versa, most applications of image and video restoration techniques, such as inpainting or denoising, aim to enhance the quality of experience of human viewers. Correctly predicting the similarity of an image with an undistorted reference image, as subjectively experienced by a human viewer, can thus lead to significant improvements in any transmission, compression, or restoration system. This paper introduces the Haar wavelet-based perceptual similarity index (HaarPSI), a novel and easy-to-compute similarity measure for full reference image quality assessment. HaarPSI utilizes the coefficients obtained from a Haar wavelet decomposition to assess local similarities between two images, as well as the relative importance of image areas. The consistency of HaarPSI with human quality of experience was validated on four large benchmark databases containing several thousands of differently distorted images. On these databases, HaarPSI achieves higher correlations with human opinion scores than state-of-the-art full reference similarity measures like the structural similarity index (SSIM), the feature similarity index (FSIM), and the visual saliency-based index (VSI). Along with the simple computational structure and the short execution time, these promising experimental results suggest a high applicability of HaarPSI in real world tasks.
image-analysis  metrics  wavelets  representation  rather-interesting  feature-construction  nudge-targets  consider:feature-discovery 
9 days ago
[1608.03542] WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia
We present WikiReading, a large-scale natural language understanding task and publicly-available dataset with 18 million instances. The task is to predict textual values from the structured knowledge base Wikidata by reading the text of the corresponding Wikipedia articles. The task contains a rich variety of challenging classification and extraction sub-tasks, making it well-suited for end-to-end models such as deep neural networks (DNNs). We compare various state-of-the-art DNN-based architectures for document classification, information extraction, and question answering. We find that models supporting a rich answer space, such as word or character sequences, perform best. Our best-performing model, a word-level sequence to sequence model with a mechanism to copy out-of-vocabulary words, obtains an accuracy of 71.8%.
natural-language-processing  machine-learning  dataset  open-source  nudge-targets  consider:representation  consider:performance-measures 
9 days ago
[1701.09097] An Intermediate Level of Abstraction for Computational Systems Chemistry
Computational techniques are required for narrowing down the vast space of possibilities to plausible prebiotic scenarios, since precise information on the molecular composition, the dominant reaction chemistry, and the conditions for that era are scarce. The exploration of large chemical reaction networks is a central aspect in this endeavour. While quantum chemical methods can accurately predict the structures and reactivities of small molecules, they are not efficient enough to cope with large-scale reaction systems. The formalization of chemical reactions as graph grammars provides a generative system, well grounded in category theory, at the right level of abstraction for the analysis of large and complex reaction networks. An extension of the basic formalism into the realm of integer hyperflows allows for the identification of complex reaction patterns, such as auto-catalysis, in large reaction networks using optimization techniques.
cheminformatics  graph-theory  representation  network-theory  hey-I-know-this-guy  complexology 
9 days ago
[1701.09123] Robust Multilingual Named Entity Recognition with Shallow Semi-Supervised Features
We present a multilingual Named Entity Recognition approach based on a robust and general set of features across languages and datasets. Our system combines shallow local information with clustering semi-supervised features induced on large amounts of unlabeled text. Understanding via empirical experimentation how to effectively combine various types of clustering features allows us to seamlessly export our system to other datasets and languages. The result is a simple but highly competitive system which obtains state of the art results across five languages and twelve datasets. The results are reported on standard shared task evaluation data such as CoNLL for English, Spanish and Dutch. Furthermore, and despite the lack of linguistically motivated features, we also report best results for languages such as Basque and German. In addition, we demonstrate that our method also obtains very competitive results even when the amount of supervised data is cut by half, alleviating the dependency on manually annotated data. Finally, the results show that our emphasis on clustering features is crucial to develop robust out-of-domain models. The system and models are freely available to facilitate its use and guarantee the reproducibility of results.
natural-language-processing  classification  algorithms  machine-learning  rather-interesting  linguistics  corpus  learning-from-data  nudge-targets  consider:feature-discovery  data-fusion 
9 days ago
[1605.08313] A Light-powered, Always-On, Smart Camera with Compressed Domain Gesture Detection
In this paper we propose an energy-efficient camera-based gesture recognition system powered by light energy for "always on" applications. Low energy consumption is achieved by directly extracting gesture features from the compressed measurements, which are the block averages and the linear combinations of the image sensor's pixel values. The gestures are recognized using a nearest-neighbour (NN) classifier followed by Dynamic Time Warping (DTW). The system has been implemented on an Analog Devices Black Fin ULP vision processor and powered by PV cells whose output is regulated by TI's DC-DC buck converter with Maximum Power Point Tracking (MPPT). Measured data reveals that with only 400 compressed measurements (768x compression ratio) per frame, the system is able to recognize key wake-up gestures with greater than 80% accuracy and only 95mJ of energy per frame. Owing to its fully self-powered operation, the proposed system can find wide applications in "always-on" vision systems such as in surveillance, robotics and consumer electronics with touch-less operation.
engineering-design  photography  circuits  rather-interesting 
9 days ago
[1610.08597] Word Embeddings to Enhance Twitter Gang Member Profile Identification
Gang affiliates have joined the masses who use social media to share thoughts and actions publicly. Interestingly, they use this public medium to express recent illegal actions, to intimidate others, and to share outrageous images and statements. Agencies able to unearth these profiles may thus be able to anticipate, stop, or hasten the investigation of gang-related crimes. This paper investigates the use of word embeddings to help identify gang members on Twitter. Building on our previous work, we generate word embeddings that translate what Twitter users post in their profile descriptions, tweets, profile images, and linked YouTube content to a real vector format amenable for machine learning classification. Our experimental results show that pre-trained word embeddings can boost the accuracy of supervised learning algorithms trained over gang members social media posts.
social-networks  statistics  kinda-scary  feature-extraction  natural-language-processing  Twitter  seeing-like-a-state 
10 days ago
[1312.5542] Word Emdeddings through Hellinger PCA
Word embeddings resulting from neural language models have been shown to be successful for a large variety of NLP tasks. However, such architecture might be difficult to train and time-consuming. Instead, we propose to drastically simplify the word embeddings computation through a Hellinger PCA of the word co-occurence matrix. We compare those new word embeddings with some well-known embeddings on NER and movie review tasks and show that we can reach similar or even better performance. Although deep learning is not really necessary for generating good word embeddings, we show that it can provide an easy way to adapt embeddings to specific tasks.
natural-language-processing  preprocessing  representation  rather-interesting  algorithms 
10 days ago
[1702.00318] A Hybrid Evolutionary Algorithm Based on Solution Merging for the Longest Arc-Preserving Common Subsequence Problem
The longest arc-preserving common subsequence problem is an NP-hard combinatorial optimization problem from the field of computational biology. This problem finds applications, in particular, in the comparison of arc-annotated Ribonucleic acid (RNA) sequences. In this work we propose a simple, hybrid evolutionary algorithm to tackle this problem. The most important feature of this algorithm concerns a crossover operator based on solution merging. In solution merging, two or more solutions to the problem are merged, and an exact technique is used to find the best solution within this union. It is experimentally shown that the proposed algorithm outperforms a heuristic from the literature.
combinatorics  bioinformatics  metaheuristics  strings  rather-interesting  nudge-targets  consider:looking-to-see  consider:representation 
10 days ago
[1611.05546] Zero-Shot Visual Question Answering
Part of the appeal of Visual Question Answering (VQA) is its promise to answer new questions about previously unseen images. Most current methods demand training questions that illustrate every possible concept, and will therefore never achieve this capability, since the volume of required training data would be prohibitive. Answering general questions about images requires methods capable of Zero-Shot VQA, that is, methods able to answer questions beyond the scope of the training questions. We propose a new evaluation protocol for VQA methods which measures their ability to perform Zero-Shot VQA, and in doing so highlights significant practical deficiencies of current approaches, some of which are masked by the biases in current datasets. We propose and evaluate several strategies for achieving Zero-Shot VQA, including methods based on pretrained word embeddings, object classifiers with semantic embeddings, and test-time retrieval of example images. Our extensive experiments are intended to serve as baselines for Zero-Shot VQA, and they also achieve state-of-the-art performance in the standard VQA evaluation setting.
machine-learning  image-processing  image-analysis  deep-learning  algorithms  rather-interesting  natural-language-processing  artificial-intelligence  to-write-about  consider:representation 
10 days ago
A City Is Not a Computer
We must also recognize the shortcomings in models that presume the objectivity of urban data and conveniently delegate critical, often ethical decisions to the machine. We, humans, make urban information by various means: through sensory experience, through long-term exposure to a place, and, yes, by systematically filtering data. It’s essential to make space in our cities for those diverse methods of knowledge production. And we have to grapple with the political and ethical implications of our methods and models, embedded in all acts of planning and design. City-making is always, simultaneously, an enactment of city-knowing — which cannot be reduced to computation.
urban-planning  technocracy  learning  modeling-is-not-mathematics  social-dynamics  theory-and-practice-sitting-in-a-tree  to-write-about  via:arthegall 
10 days ago
[1701.08982] Leaf-reconstructibility of phylogenetic networks
An important problem in evolutionary biology is to reconstruct the evolutionary history of a set X of species. This history is often represented as a phylogenetic network, that is, a connected graph with leaves labelled by elements in X (for example, an evolutionary tree), which is usually also binary, i.e. all vertices have degree 1 or 3. A common approach used in phylogenetics to build a phylogenetic network on X involves constructing it from networks on subsets of X. Here we consider the question of which (unrooted) phylogenetic networks are leaf-reconstructible, i.e. which networks can be uniquely reconstructed from the set of networks obtained from it by deleting a single leaf (its X-deck). This problem is closely related to the (in)famous reconstruction conjecture in graph theory but, as we shall show, presents distinct challenges. We show that some large classes of phylogenetic networks are reconstructible from their X-deck. This includes phylogenetic trees, binary networks containing at least one non-trivial cut-edge, and binary level-4 networks (the level of a network measures how far it is from being a tree). We also show that for fixed k, almost all binary level-k phylogenetic networks are leaf-reconstructible. As an application of our results, we show that a level-3 network N can be reconstructed from its quarnets, that is, 4-leaved networks that are induced by N in a certain recursive fashion. Our results lead to several interesting open problems which we discuss, including the conjecture that all phylogenetic networks with at least five leaves are leaf-reconstructible.
cladistics  phylogenetics  combinatorics  algorithms  rather-interesting  constructibility  proof  nudge-targets  consider:looking-to-see  consider:representation 
10 days ago
[1701.00951] A Concave Optimization Algorithm for Matching Partially Overlapping Point Sets
Point matching refers to the process of finding spatial transformation and correspondences between two sets of points. In this paper, we focus on the case that there is only partial overlap between two point sets. Following the approach of the robust point matching method, we model point matching as a mixed linear assignment-least square problem and show that after eliminating the transformation variable, the resulting problem of minimization with respect to point correspondence is a concave optimization problem. Furthermore, this problem has the property that the objective function can be converted into a form with few nonlinear terms via a linear transformation. Based on these properties, we employ the branch-and-bound (BnB) algorithm to optimize the resulting problem where the dimension of the search space is small. To further improve efficiency of the BnB algorithm where computation of the lower bound is the bottleneck, we propose a new lower bounding scheme which has a k-cardinality linear assignment formulation and can be efficiently solved. Experimental results show that the proposed algorithm outperforms state-of-the-art methods in terms of robustness to disturbances and point matching accuracy.
point-set-registration  optimization  nonlinear-dynamics  numerical-methods  performance-measure  rather-interesting  nudge-targets  consider:looking-to-see 
10 days ago
[1202.4831] Formalization and Implementation of Algebraic Methods in Geometry
We describe our ongoing project of formalization of algebraic methods for geometry theorem proving (Wu's method and the Groebner bases method), their implementation and integration in educational tools. The project includes formal verification of the algebraic methods within Isabelle/HOL proof assistant and development of a new, open-source Java implementation of the algebraic methods. The project should fill-in some gaps still existing in this area (e.g., the lack of formal links between algebraic methods and synthetic geometry and the lack of self-contained implementations of algebraic methods suitable for integration with dynamic geometry tools) and should enable new applications of theorem proving in education.
artificial-intelligence  representation  plane-geometry  traditional-methods  nudge-targets  consider:representation 
10 days ago
[1207.4432] Towards Understanding Triangle Construction Problems
Straightedge and compass construction problems are one of the oldest and most challenging problems in elementary mathematics. The central challenge, for a human or for a computer program, in solving construction problems is a huge search space. In this paper we analyze one family of triangle construction problems, aiming at detecting a small core of the underlying geometry knowledge. The analysis leads to a small set of needed definitions, lemmas and primitive construction steps, and consequently, to a simple algorithm for automated solving of problems from this family. The same approach can be applied to other families of construction problems.
plane-geometry  representation  artificial-intelligence  to-write-about  nudge-targets 
10 days ago
[1701.08883] A Covert Queueing Channel in Round Robin Schedulers
We study a covert queueing channel between two users sharing a round robin scheduler. Such a covert channel can arise when users share a resource such as a computer processor or a router arbitrated by a round robin policy. We present an information-theoretic framework to model and derive the maximum reliable data transmission rate, i.e., the capacity of this channel for both noiseless and noisy scenarios. Our results show that seemingly isolated users can communicate with high rate over the covert channel. Furthermore, we propose a practical finite-length code construction, which achieves the capacity limit.
secret-messages  rather-interesting  amusing  mathematical-recreations  to-write-about  exaptation  nonlinear-dynamics  information-theory  consider:agent-based  consider:looking-to-see 
10 days ago
[1612.07234] Ensembles of self-avoiding polygons
We consider an ensemble of self-avoiding polygons penalized by the cumulative length. Such an ensemble can be viewed as random permutations of the vertices of a graph such that every vertex is either mapped to a neighbour with a penalization factor α or it is mapped to itself with no penalization. If μ is the cyclic connective constant of an infinite vertex-transitive graph, we prove non-existence of long cycles (resp. long polygons) for all α>αc, where αc<logμ. This shows that, at least for α∈(αc,logμ), a self-avoiding polygon embedded into an ensemble of other self-avoiding polygons behaves quite different from the single self-avoiding polygon. In the case where the graph is the d-dimensional cubic lattice, we further show that when a cycle is forced through the system, it converges to a straight line in the scaling limit. More specifically, we prove that the length of the open cycle is at most n+O(n‾√logn) when α is large enough.
sooooo-mathy  probability-theory  self-avoiding-things  to-write-about  consider:heuristics  consider:looking-to-see 
12 days ago
[1502.05767] Automatic differentiation in machine learning: a survey
Derivatives, mostly in the form of gradients and Hessians, are ubiquitous in machine learning. Automatic differentiation (AD) is a technique for calculating derivatives of numeric functions expressed as computer programs efficiently and accurately, used in fields such as computational fluid dynamics, nuclear engineering, and atmospheric sciences. Despite its advantages and use in other fields, machine learning practitioners have been little influenced by AD and make scant use of available tools. We survey the intersection of AD and machine learning, cover applications where AD has the potential to make a big impact, and report on some recent developments in the adoption of this technique. We aim to dispel some misconceptions that we contend have impeded the use of AD within the machine learning community.
numerical-methods  algorithms  rather-interesting  to-write-about  consider:GP  review  via:numerous 
12 days ago
[1603.02754] XGBoost: A Scalable Tree Boosting System
Tree boosting is a highly effective and widely used machine learning method. In this paper, we describe a scalable end-to-end tree boosting system called XGBoost, which is used widely by data scientists to achieve state-of-the-art results on many machine learning challenges. We propose a novel sparsity-aware algorithm for sparse data and weighted quantile sketch for approximate tree learning. More importantly, we provide insights on cache access patterns, data compression and sharding to build a scalable tree boosting system. By combining these insights, XGBoost scales beyond billions of examples using far fewer resources than existing systems.
machine-learning  algorithms  boosting  nudge-targets  consider:integration  consider:looking-to-see 
14 days ago
schenker/image-learner: Training a neural network to map from x,y of an images pixels to r,g,b.
Train a neural network to map from x and y coordinate of each pixel to the pixels r,g,b values. The network has 2 inputs (x and y), several fully connected (highway) layers and three outputs (r, g and b).
generative-art  rather-interesting  nudge-targets  consider:looking-to-see  to-write-about 
14 days ago
[1701.03329] A Data-Oriented Model of Literary Language
We consider the task of predicting how literary a text is, with a gold standard from human ratings. Aside from a standard bigram baseline, we apply rich syntactic tree fragments, mined from the training set, and a series of hand-picked features. Our model is the first to distinguish degrees of highly and less literary novels using a variety of lexical and syntactic features, and explains 76.0 % of the variation in literary ratings.
digital-humanities  rather-interesting  feature-construction  feature-extraction  natural-language-processing  aesthetics  to-write-about  nudge-targets  consider:looking-to-see 
14 days ago
[1612.08242] YOLO9000: Better, Faster, Stronger
We introduce YOLO9000, a state-of-the-art, real-time object detection system that can detect over 9000 object categories. First we propose various improvements to the YOLO detection method, both novel and drawn from prior work. The improved model, YOLOv2, is state-of-the-art on standard detection tasks like PASCAL VOC and COCO. At 67 FPS, YOLOv2 gets 76.8 mAP on VOC 2007. At 40 FPS, YOLOv2 gets 78.6 mAP, outperforming state-of-the-art methods like Faster RCNN with ResNet and SSD while still running significantly faster. Finally we propose a method to jointly train on object detection and classification. Using this method we train YOLO9000 simultaneously on the COCO detection dataset and the ImageNet classification dataset. Our joint training allows YOLO9000 to predict detections for object classes that don't have labelled detection data. We validate our approach on the ImageNet detection task. YOLO9000 gets 19.7 mAP on the ImageNet detection validation set despite only having detection data for 44 of the 200 classes. On the 156 classes not in COCO, YOLO9000 gets 16.0 mAP. But YOLO can detect more than just 200 classes; it predicts detections for more than 9000 different object categories. And it still runs in real-time.
deep-learning  horse-races  machine-learning  image-segmentation  image-analysis  video  nudge-targets  consider:feature-discovery  consider:performance-measures 
14 days ago
Your favorite color makes learning more adaptable and precise | bioRxiv
Learning from reward feedback is essential for survival but can become extremely challenging when choice options have multiple features and feature values (curse of dimensionality). Here, we propose a general framework for learning reward values in dynamic multi-dimensional environments via encoding and updating the average value of individual features. We predicted that this feature-based learning occurs not just because it can reduce dimensionality, but more importantly because it can increase adaptability without compromising precision. We experimentally tested this novel prediction and found that in dynamic environments, human subjects adopted feature-based learning even when this approach does not reduce dimensionality. Even in static low-dimensional environment, subjects initially tended to adopt feature-based learning and switched to learning individual option values only when feature values could not accurately predict all objects values. Moreover, behaviors of two alternative network models demonstrated that hierarchical decision-making and learning could account for our experimental results and thus provides a plausible mechanism for model adoption during learning in dynamic environments. Our results constrain neural mechanisms underlying learning in dynamic multi-dimensional environments, and highlight the importance of neurons encoding the value of individual features in this learning.
machine-learning  curse-of-dimensionality  feature-construction  rather-interesting  approximation  nudge-targets  consider:feature-discovery 
14 days ago
[1701.01329] Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks
In de novo drug design, computational strategies are used to generate novel molecules with good affinity to the desired biological target. In this work, we show that recurrent neural networks can be trained as generative models for molecular structures, similar to statistical language models in natural language processing. We demonstrate that the properties of the generated molecules correlate very well with the properties of the molecules used to train the model. In order to enrich libraries with molecules active towards a given biological target, we propose to fine-tune the model with small sets of molecules, which are known to be active against that target.
Against Staphylococcus aureus, the model reproduced 14% of 6051 hold-out test molecules that medicinal chemists designed, whereas against Plasmodium falciparum (Malaria) it reproduced 28% of 1240 test molecules. When coupled with a scoring function, our model can perform the complete de novo drug design cycle to generate large sets of novel molecules for drug discovery.
pharmaceutical  engineering-design  machine-learning  neural-networks  feature-construction  nudge-targets  consider:representation  consider:looking-to-see  looking-to-see  cheminformatics  party-like-its-1999 
14 days ago
[1605.06537] You never surf alone. Ubiquitous tracking of users' browsing habits
In the early age of the internet users enjoyed a large level of anonymity. At the time web pages were just hypertext documents; almost no personalisation of the user experience was o ered. The Web today has evolved as a world wide distributed system following specific architectural paradigms. On the web now, an enormous quantity of user generated data is shared and consumed by a network of applications and services, reasoning upon users expressed preferences and their social and physical connections. Advertising networks follow users' browsing habits while they surf the web, continuously collecting their traces and surfing patterns. We analyse how users tracking happens on the web by measuring their online footprint and estimating how quickly advertising networks are able to pro le users by their browsing habits.
advertising  social-networks  inference  algorithms  privacy 
14 days ago
[1510.07584] Edge conflicts do not determine geodesics in the associahedron
There are no known efficient algorithms to calculate distance in the one-skeleta of associahedra, a problem which is equivalent to finding rotation distance between rooted binary trees or the flip distance between polygonal trianguations. One measure of the difference between trees is the number of conflicting edge pairs, and a natural way of trying to find short paths is to minimize successively this number of conflicting edge pairs using flip operations in the corresponding triangulations. We describe examples which show that the number of such conflicts does not always decrease along geodesics. Thus, a greedy algorithm which always chooses a transformation which reduces conflicts will not produce a geodesic in all cases. Further, there are examples of increasing size showing that the number of conflicts can increase by any specified amount.
combinatorics  rather-interesting  metrics  open-questions  nudge-targets  consider:looking-to-see  to-write-about  consider:performance-measures  consider:robustness 
14 days ago
[1506.02640] You Only Look Once: Unified, Real-Time Object Detection
We present YOLO, a new approach to object detection. Prior work on object detection repurposes classifiers to perform detection. Instead, we frame object detection as a regression problem to spatially separated bounding boxes and associated class probabilities. A single neural network predicts bounding boxes and class probabilities directly from full images in one evaluation. Since the whole detection pipeline is a single network, it can be optimized end-to-end directly on detection performance.
Our unified architecture is extremely fast. Our base YOLO model processes images in real-time at 45 frames per second. A smaller version of the network, Fast YOLO, processes an astounding 155 frames per second while still achieving double the mAP of other real-time detectors. Compared to state-of-the-art detection systems, YOLO makes more localization errors but is far less likely to predict false detections where nothing exists. Finally, YOLO learns very general representations of objects. It outperforms all other detection methods, including DPM and R-CNN, by a wide margin when generalizing from natural images to artwork on both the Picasso Dataset and the People-Art Dataset.
machine-learning  image-segmentation  architecture  algorithms  nudge-targets  consider:representation 
14 days ago
Against Normalization: The Lesson of the “Munich Post” - Los Angeles Review of Books
I had to search another Munich archive to find the very final issues of the Munich Post, but they were even more dispiriting than I could imagine. The paper went down fighting a lie, fighting Nazi murderers, refusing to normalize the Hitler regime.
A week after Hitler came to power on January 30, 1933, the Munich Post published their regular murder survey under the headline “Nazi Party Hands Dripping with Blood,” enumerating the bloody casualties: 18 dead, 34 wounded in street battles with the SA Stormtroopers.
These are the headlines that followed in daily succession:
“Germany Under the Hitler Regime: Political Murder and Terror”
“Blood Guilt of the Nazi Party”
“Germany Today: No Day Without Death”
“Brutal Terror in the Streets of Munich”
“Outlaws and Murderers in Power”
“People Allow Themselves to Be Intimidated”
The era of normalization had begun everywhere else, but the Munich Post resisted.
The Munich Post lost, yes. Soon their office was closed. Some of the journalists ended up in Dachau, some “disappeared.” But they’d won a victory for truth. A victory over normalization. They never stopped fighting the lies, big and small, and left a record of defiance that was heroic and inspirational. They discovered the truth about “endlösung” before most could have even imagined it. The truth is always worth knowing. Support your local journalist.
history  fascism  media 
14 days ago
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