12112
[1705.04353] On the records
World record setting has long attracted public interest and scientific investigation. Extremal records summarize the limits of the space explored by a process, and the historical progression of a record sheds light on the underlying dynamics of the process. Existing analyses of prediction, statistical properties, and ultimate limits of record progressions have focused on particular domains. However, a broad perspective on how record progressions vary across different spheres of activity needs further development. Here we employ cross-cutting metrics to compare records across a variety of domains, including sports, games, biological evolution, and technological development. We find that these domains exhibit characteristic statistical signatures in terms of rates of improvement, "burstiness" of record-breaking time series, and the acceleration of the record breaking process. Specifically, sports and games exhibit the slowest rate of improvement and a wide range of rates of "burstiness." Technology improves at a much faster rate and, unlike other domains, tends to show acceleration in records. Many biological and technological processes are characterized by constant rates of improvement, showing less burstiness than sports and games. It is important to understand how these statistical properties of record progression emerge from the underlying dynamics. Towards this end, we conduct a detailed analysis of a particular record-setting event: elite marathon running. In this domain, we find that studying record-setting data alone can obscure many of the structural properties of the underlying process. The marathon study also illustrates how some of the standard statistical assumptions underlying record progression models may be inappropriate or commonly violated in real-world datasets.
extreme-values  time-series  feature-extraction  rather-interesting  dynamical-systems  to-understand 
yesterday
[1805.07360] Prediction in Projection: A new paradigm in delay-coordinate reconstruction
Delay-coordinate embedding is a powerful, time-tested mathematical framework for reconstructing the dynamics of a system from a series of scalar observations. Most of the associated theory and heuristics are overly stringent for real-world data, however, and real-time use is out of the question due to the expert human intuition needed to use these heuristics correctly. The approach outlined in this thesis represents a paradigm shift away from that traditional approach. I argue that perfect reconstructions are not only unnecessary for the purposes of delay-coordinate based forecasting, but that they can often be less effective than reduced-order versions of those same models. I demonstrate this using a range of low- and high-dimensional dynamical systems, showing that forecast models that employ imperfect reconstructions of the dynamics---i.e., models that are not necessarily true embeddings---can produce surprisingly accurate predictions of the future state of these systems. I develop a theoretical framework for understanding why this is so. This framework, which combines information theory and computational topology, also allows one to quantify the amount of predictive structure in a given time series, and even to choose which forecast method will be the most effective for those data.
nonlinear-dynamics  representation  complexology  rather-interesting  to-write-about  to-understand 
yesterday
[1806.01387] New And Surprising Ways to Be Mean. Adversarial NPCs with Coupled Empowerment Minimisation
Creating Non-Player Characters (NPCs) that can react robustly to unforeseen player behaviour or novel game content is difficult and time-consuming. This hinders the design of believable characters, and the inclusion of NPCs in games that rely heavily on procedural content generation. We have previously addressed this challenge by means of empowerment, a model of intrinsic motivation, and demonstrated how a coupled empowerment maximisation (CEM) policy can yield generic, companion-like behaviour. In this paper, we extend the CEM framework with a minimisation policy to give rise to adversarial behaviour. We conduct a qualitative, exploratory study in a dungeon-crawler game, demonstrating that CEM can exploit the affordances of different content facets in adaptive adversarial behaviour without modifications to the policy. Changes to the level design, underlying mechanics and our character's actions do not threaten our NPC's robustness, but yield new and surprising ways to be mean.
hey-I-know-this-guy  coevolution  evolutionary-algorithms  engineering-design  rather-interesting  to-write-about 
yesterday
Symmathesy: A Word in Progress | norabateson
I would like to propose a new word for “System” that refers specifically to living systems – that is, to systems which emerge from the communications and interactions of living vitae (another new term, one which will be defined later). The new word, and concept, for “system” that I propose is one which highlights the expression and communication of interdependency and, particularly, mutual learning. The existing word, “system”, while useful for discussion of many kinds of systems, does not communicate contextual fields of simultaneous learning as is necessary for life. The inclusion of mutual learning in the terminology is specifically meant to preclude the models of engineering and mechanism that are implicit in much systems theorizing today.   We have learned that when dealing with living systems, the many variables of developing interaction become untenable to consider in such mechanistic parameters. This change in concept should spark a significant shift in our work, in the sciences, applied professions, communication, arts, that addresses or depends upon our understanding of life and evolution. The discourse with which we discuss and study the living world should be representative of the living world, and should cautiously avoid connotations that imply or are derived from engineering.

The notion of systems as being an arrangement of parts and wholes has become a distraction from the new systemic vision, which we are trying to encourage, that sees life as relational mutual learning contexts. As studies ranging from cognitive science to epigenetics, social science, ecology and evolutionary theory, are increasingly showing, evolution emerges in interrelationality, not in arrangement. Therefore the need is acute to create a differentiation between living systems and other systems.
complexology  representation  define-your-terms  rather-interesting  to-write-about  philosophy-of-science 
yesterday
Philip Larkin, Programmer – Timothy – Medium
I make a sharp reply,
Then rebase my branch. I’m glad I can’t explain 
What insufficient docs their katas are; 
You may have thought things would come right again
If someone’d only merge your PR.
poems  in-the-style-of 
yesterday
Kumaraswamy distribution: a beta-like probability density
Maybe the algorithm I suggested for picking parameters is not very good, but I suspect the optimal parameters are not much better. Rather than saying that the Kumaraswamy distribution approximates the beta distribution, I’d say that the Kumaraswamy distribution is capable of assuming roughly the same shapes as the beta distribution. If the only reason you’re using a beta distribution is to get a certain density shape, the Kumaraswamy distribution would be a reasonable alternative. But if you need to approximate a beta distribution closely, it may not work well enough.
probability-theory  representation  rather-interesting  to-write-about  consider:feature-discovery  consider:heuristics  consider:approximation 
yesterday
[1805.11813] Derivatives of Turing machines in Linear Logic
We calculate denotations under the Sweedler semantics of the Ehrhard-Regnier derivatives of various encodings of Turing machines into linear logic. We show that these derivatives calculate the rate of change of probabilities naturally arising in the Sweedler semantics of linear logic proofs. The resulting theory is applied to the problem of synthesising Turing machines by gradient descent.
computer-science  representation  to-understand  rather-interesting 
yesterday
[1805.10872] DeepProbLog: Neural Probabilistic Logic Programming
We introduce DeepProbLog, a probabilistic logic programming language that incorporates deep learning by means of neural predicates. We show how existing inference and learning techniques can be adapted for the new language. Our experiments demonstrate that DeepProbLog supports both symbolic and subsymbolic representations and inference, 1) program induction, 2) probabilistic (logic) programming, and 3) (deep) learning from examples. To the best of our knowledge, this work is the first to propose a framework where general-purpose neural networks and expressive probabilistic-logical modeling and reasoning are integrated in a way that exploits the full expressiveness and strengths of both worlds and can be trained end-to-end based on examples.
deep-learning  representation  probabilistic-programming  rather-interesting  to-understand 
8 days ago
[1806.02717] Gamorithm
Examining games from a fresh perspective we present the idea of game-inspired and game-based algorithms, dubbed "gamorithms".
hey-I-know-this-guy  machine-learning  philosophy-of-engineering  representation  to-write-about 
8 days ago
[1805.09966] Prestige drives epistemic inequality in the diffusion of scientific ideas
The spread of ideas in the scientific community is often viewed as a competition, in which good ideas spread further because of greater intrinsic fitness. As a result, it is commonly believed that publication venue and citation counts correlate with importance and impact. However, relatively little is known about how structural factors influence the spread of ideas, and specifically how where an idea originates can influence how it spreads. Here, we investigate the role of faculty hiring networks, which embody the set of researcher transitions from doctoral to faculty institutions, in shaping the spread of ideas in computer science, and the importance of where in the network an idea originates. We consider comprehensive data on the hiring events of 5,032 faculty at all 205 Ph.D.-granting departments of computer science in the U.S. and Canada, and on the timing and titles of 200,476 associated publications. Analyzing three popular research topics, we show empirically that faculty hiring plays a significant role in driving the spread of ideas across the community. We then use epidemic models to simulate the generic spread of research ideas and quantify the consequences of where an idea originates on its longterm diffusion across the network. We find that research from prestigious institutions spreads more quickly and completely than work of similar quality originating from less prestigious institutions. Our analyses establish the theoretical trade-offs between university prestige and the quality of ideas necessary for efficient circulation. These results suggest a lower bound for epistemic inequality, identify a mechanism for the persistent epistemic advantage observed for elite institutions, and highlight limitations for meritocratic ideals.
social-networks  citation  epidemiology-of-ideas  credentialing  who-reads-who  to-write-about  rather-interesting  academic-culture  meritocracy 
8 days ago
[1805.12244] Mining gold from implicit models to improve likelihood-free inference
Simulators often provide the best description of real-world phenomena; however, they also lead to challenging inverse problems because the density they implicitly define is often intractable. We present a new suite of simulation-based inference techniques that go beyond the traditional Approximate Bayesian Computation approach, which struggles in a high-dimensional setting, and extend methods that use surrogate models based on neural networks. We show that additional information, such as the joint likelihood ratio and the joint score, can often be extracted from simulators and used to augment the training data for these surrogate models. Finally, we demonstrate that these new techniques are more sample efficient and provide higher-fidelity inference than traditional methods.
machine-learning  simulation  representation  randomness  to-understand  to-write-about 
8 days ago
[1805.09460] Cautious Deep Learning
Most classifiers operate by selecting the maximum of an estimate of the conditional distribution p(y|x) where x stands for the features of the instance to be classified and y denotes its label. This often results in a hubristic bias: overconfidence in the assignment of a definite label. Usually, the observations are concentrated on a small volume but the classifier provides definite predictions for the entire space. We propose constructing conformal prediction sets [vovk2005algorithmic] which contain a set of labels rather than a single label. These conformal prediction sets contain the true label with probability 1−α. Our construction is based on p(x|y) rather than p(y|x) which results in a classifier that is very cautious: it outputs the null set - meaning `I don't know' --- when the object does not resemble the training examples. An important property of our approach is that classes can be added or removed without having to retrain the classifier. We demonstrate the performance on the ImageNet ILSVRC dataset using high dimensional features obtained from state of the art convolutional neural networks.
define-your-terms  representation  rather-interesting  machine-learning  conservative-estimates  performance-measure  to-write-about 
8 days ago
[1806.04510] Dank Learning: Generating Memes Using Deep Neural Networks
We introduce a novel meme generation system, which given any image can produce a humorous and relevant caption. Furthermore, the system can be conditioned on not only an image but also a user-defined label relating to the meme template, giving a handle to the user on meme content. The system uses a pretrained Inception-v3 network to return an image embedding which is passed to an attention-based deep-layer LSTM model producing the caption - inspired by the widely recognised Show and Tell Model. We implement a modified beam search to encourage diversity in the captions. We evaluate the quality of our model using perplexity and human assessment on both the quality of memes generated and whether they can be differentiated from real ones. Our model produces original memes that cannot on the whole be differentiated from real ones.
neural-networks  generative-art  generative-models  rather-interesting  amusing  to-write-about 
8 days ago
[1803.06824] Indeterminism in Physics, Classical Chaos and Bohmian Mechanics. Are Real Numbers Really Real?
It is usual to identify initial conditions of classical dynamical systems with mathematical real numbers. However, almost all real numbers contain an infinite amount of information. Since a finite volume of space can't contain more than a finite amount of information, I argue that the mathematical real numbers are not physically relevant. Moreover, a better terminology for the so-called real numbers is "random numbers", as their series of bits are truly random. I propose an alternative classical mechanics, which is empirically equivalent to classical mechanics, but uses only finite-information numbers. This alternative classical mechanics is non-deterministic, despite the use of deterministic equations, in a way similar to quantum theory. Interestingly, both alternative classical mechanics and quantum theories can be supplemented by additional variables in such a way that the supplemented theory is deterministic. Most physicists straightforwardly supplement classical theory with real numbers to which they attribute physical existence, while most physicists reject Bohmian mechanics as supplemented quantum theory, arguing that Bohmian positions have no physical reality. I argue that it is more economical and natural to accept non-determinism with potentialities as a real mode of existence, both for classical and quantum physics.
philosophy-of-science  mathematics  representation  rather-interesting  to-understand  information-theory  huh 
8 days ago
[1802.03905] How to Match when All Vertices Arrive Online
We introduce a fully online model of maximum cardinality matching in which all vertices arrive online. On the arrival of a vertex, its incident edges to previously-arrived vertices are revealed. Each vertex has a deadline that is after all its neighbors' arrivals. If a vertex remains unmatched until its deadline, the algorithm must then irrevocably either match it to an unmatched neighbor, or leave it unmatched. The model generalizes the existing one-sided online model and is motivated by applications including ride-sharing platforms, real-estate agency, etc.
We show that the Ranking algorithm by Karp et al. (STOC 1990) is 0.5211-competitive in our fully online model for general graphs. Our analysis brings a novel charging mechanic into the randomized primal dual technique by Devanur et al. (SODA 2013), allowing a vertex other than the two endpoints of a matched edge to share the gain. To our knowledge, this is the first analysis of Ranking that beats 0.5 on general graphs in an online matching problem, a first step towards solving the open problem by Karp et al. (STOC 1990) about the optimality of Ranking on general graphs. If the graph is bipartite, we show that the competitive ratio of Ranking is between 0.5541 and 0.5671. Finally, we prove that the fully online model is strictly harder than the previous model as no online algorithm can be 0.6317<1−1e-competitive in our model even for bipartite graphs.
algorithms  dynamical-systems  graph-theory  rather-interesting  computational-complexity  to-write-about  to-simulate 
12 days ago
Exploring the golden ratio Φ
This post is really just things I've learned from other people, but things that surprised me
mathematical-recreations  phi  geometry  to-write-about 
25 days ago
Home | Kappa Language
By separating a rule from a patch on which it acts we gain a much clearer approach to mechanistic causality. If causal analysis were to proceed at the level of patches, it would obfuscate the causal structure of a system by dragging along context irrelevant to an event. In addition to simulation and static analysis, the Kappa platform also extracts the causal structure of a rule system from its simulation traces.
bioinformatics  representation  hey-I-know-this-guy  complexology  pattern-discovery  rather-interesting  to-write-about 
25 days ago
Trent McConaghy - FFX
FFX is a technique for symbolic regression, to induce whitebox models given X/y training data. It does Fast Function Extraction. It is:

Fast - runtime 5-60 seconds, depending on problem size (1GHz cpu)
Scalable - 1000 input variables, no problem!
Deterministic - no need to "hope and pray".
If you ignore the whitebox-model aspect, FFX can be viewed as a regression tool. It's been used this way for thousands of industrial problems with 100K+ input variables. It can also be used as a classifier (FFXC), by wrapping the output with a logistic map. This has also been used successfully on thousands of industrial problems.
hey-I-know-this-guy  symbolic-regression  algorithms  numerical-methods  data-analysis  to-write-about 
25 days ago
Three Little Circles
Once upon a time, there were three little circles.
d3  tutorial  to-understand  javascript  visualization  for-a-project 
25 days ago
[1805.07980] Collisionless periodic orbits in the free-fall three-body problem
Although the free-fall three-body problem have been investigated for more than one century, however, only four collisionless periodic orbits have been found. In this paper, we report 234 collisionless periodic orbits of the free-fall three-body system with some mass ratios, including three known collisionless periodic orbits. Thus, 231 collisionless free-fall periodic orbits among them are entirely new. In theory, we can gain periodic orbits of the free-fall three-body system in arbitrary ratio of mass. Besides, it is found that, for a given ratio of masses of two bodies, there exists a generalized Kepler's third law for the periodic three-body system. All of these would enrich our knowledge and deepen our understanding about the famous three-body problem as a whole.
nonlinear-dynamics  stamp-collecting  rather-interesting  nudge-targets  consider:looking-to-see  consider:performance-measures 
25 days ago
[1805.02436] Combining Tools for Optimization and Analysis of Floating-Point Computations
Recent renewed interest in optimizing and analyzing floating-point programs has lead to a diverse array of new tools for numerical programs. These tools are often complementary, each focusing on a distinct aspect of numerical programming. Building reliable floating point applications typically requires addressing several of these aspects, which makes easy composition essential. This paper describes the composition of two recent floating-point tools: Herbie, which performs accuracy optimization, and Daisy, which performs accuracy verification. We find that the combination provides numerous benefits to users, such as being able to use Daisy to check whether Herbie's unsound optimizations improved the worst-case roundoff error, as well as benefits to tool authors, including uncovering a number of bugs in both tools. The combination also allowed us to compare the different program rewriting techniques implemented by these tools for the first time. The paper lays out a road map for combining other floating-point tools and for surmounting common challenges.
numerical-methods  algorithms  optimization  rather-interesting  floating-point  representation  to-understand  nudge-targets  consider:looking-to-see 
25 days ago
[1805.02213] Uniform Distribution of Kakutani Partitions Generated By Substitution Schemes
The main result of this paper is a proof of uniform distribution for a large family of sequences of partitions, constituting a generalization of a result of Kakutani regarding partitions of the unit interval. A sequence is defined according to a multiscale substitution scheme on a set of prototiles, which is a set of substitution rules determining a tiling of each prototile by rescaled copies of the prototiles at hand. Given a multiscale substitution scheme, a succession of substitutions of tiles is used to define a sequence of partitions, which is studied using a directed weighted graph associated with the scheme.
tiling  recursion  graph-theory  fractals  to-understand  rewriting-systems 
25 days ago
[1805.02274] On the $f$-Matrices of Pascal-like Triangles Defined by Riordan Arrays
We define and characterize the f-matrices associated to Pascal-like matrices that are defined by ordinary and exponential Riordan arrays. These generalize the face matrices of simplices and hypercubes. Their generating functions can be expressed simply in terms of continued fractions, which are shown to be transformations of the generating functions of the corresponding γ- and h-matrices.
combinatorics  continued-fractions  topology  to-understand  to-write-about  nudge-targets  consider:looking-to-see 
27 days ago
[1607.01117] Anagram-free Graph Colouring
An anagram is a word of the form WP where W is a non-empty word and P is a permutation of W. We study anagram-free graph colouring and give bounds on the chromatic number. Alon et al. (2002) asked whether anagram-free chromatic number is bounded by a function of the maximum degree. We answer this question in the negative by constructing graphs with maximum degree 3 and unbounded anagram-free chromatic number. We also prove upper and lower bounds on the anagram-free chromatic number of trees in terms of their radius and pathwidth. Finally, we explore extensions to edge colouring and k-anagram-free colouring.
graph-theory  algorithms  graph-coloring  feature-construction  nudge-targets  consider:looking-to-see  computational-complexity 
27 days ago
[1612.09443] Transversals in Latin arrays with many distinct symbols
An array is row-Latin if no symbol is repeated within any row. An array is Latin if it and its transpose are both row-Latin. A transversal in an n×n array is a selection of n different symbols from different rows and different columns. We prove that every n×n Latin array containing at least (2−2‾√)n2 distinct symbols has a transversal. Also, every n×n row-Latin array containing at least 14(5−5‾√)n2 distinct symbols has a transversal. Finally, we show by computation that every Latin array of order 7 has a transversal, and we describe all smaller Latin arrays that have no transversal.
combinatorics  existence-proof  rather-interesting  nudge-targets  consider:looking-to-see 
27 days ago
[1708.09571] Anagram-free colourings of graph subdivisions
An anagram is a word of the form WP where W is a non-empty word and P is a permutation of W. A vertex colouring of a graph is anagram-free if no subpath of the graph is an anagram. Anagram-free graph colouring was independently introduced by Kam\v{c}ev, {\L}uczak and Sudakov and ourselves. In this paper we introduce the study of anagram-free colourings of graph subdivisions. We show that every graph has an anagram-free 8-colourable subdivision. The number of division vertices per edge is exponential in the number of edges. For trees, we construct anagram-free 10-colourable subdivisions with fewer division vertices per edge. Conversely, we prove lower bounds, in terms of division vertices per edge, on the anagram-free chromatic number for subdivisions of the complete graph and subdivisions of complete trees of bounded degree.
combinatorics  graph-theory  graph-coloring  computational-complexity  rather-interesting  nudge-targets  consider:looking-to-see 
27 days ago
[1803.07694] Defective and Clustered Graph Colouring
Consider the following two ways to colour the vertices of a graph where the requirement that adjacent vertices get distinct colours is relaxed. A colouring has "defect" d if each monochromatic component has maximum degree at most d. A colouring has "clustering" c if each monochromatic component has at most c vertices. This paper surveys research on these types of colourings, where the first priority is to minimise the number of colours, with small defect or small clustering as a secondary goal. List colouring variants are also considered. The following graph classes are studied: outerplanar graphs, planar graphs, graphs embeddable in surfaces, graphs with given maximum degree, graphs with given maximum average degree, graphs excluding a given subgraph, graphs with linear crossing number, linklessly or knotlessly embeddable graphs, graphs with given Colin de Verdi\`ere parameter, graphs with given circumference, graphs excluding a fixed graph as an immersion, graphs with given thickness, graphs with given stack- or queue-number, graphs excluding Kt as a minor, graphs excluding Ks,t as a minor, and graphs excluding an arbitrary graph H as a minor. Several open problems are discussed.
combinatorics  graph-theory  algorithms  rather-interesting  computational-complexity  nudge-targets  consider:performance-measures 
27 days ago
[1805.02356] Multimodal Machine Translation with Reinforcement Learning
Multimodal machine translation is one of the applications that integrates computer vision and language processing. It is a unique task given that in the field of machine translation, many state-of-the-arts algorithms still only employ textual information. In this work, we explore the effectiveness of reinforcement learning in multimodal machine translation. We present a novel algorithm based on the Advantage Actor-Critic (A2C) algorithm that specifically cater to the multimodal machine translation task of the EMNLP 2018 Third Conference on Machine Translation (WMT18). We experiment our proposed algorithm on the Multi30K multilingual English-German image description dataset and the Flickr30K image entity dataset. Our model takes two channels of inputs, image and text, uses translation evaluation metrics as training rewards, and achieves better results than supervised learning MLE baseline models. Furthermore, we discuss the prospects and limitations of using reinforcement learning for machine translation. Our experiment results suggest a promising reinforcement learning solution to the general task of multimodal sequence to sequence learning.
natural-language-processing  machine-learning  multitask-learning  rather-interesting  algorithms  performance-measure  to-write-about 
27 days ago
With Great Power Comes Poor Latent Codes: Representation Learning in VAEs (Pt. 2)
A machine learning idea I find particularly compelling is that of embeddings, representations, encodings: all of these vector spaces that can seem nigh-on magical when you zoom in and see the ways that a web of concepts can be beautifully mapped into mathematical space. I’ve spent enough time in the weeds of parameter optimization and vector algebra to know that calling any aspect of machine learning “magical” is starry-eyed even as I say it, but: approaches like this are unavoidably tantalizing because they offer the possibility of finding some optimal representation of concepts, a “optimal mathematical language” with which we can feed all of the world’s information to our machines.
machine-learning  the-mangle-in-practice  neural-networks  representation  rather-interesting  to-write-about 
27 days ago
Foot-candles: the different paths to tech – Alice Goldfuss
The deeper you dive into programming, the more you will run into topics covered by CS degrees. This may make you feel extremely behind and out of your depth. When this happens, keep the following in mind:

Your lack of knowledge in these topics doesn’t negate the work you’ve already done.
You know things CS grads don’t.
It’s likely your understanding of the topic is fresher and more complete than a CS grad who hasn’t touched it in years.
Everyone learns things in different orders and at different times, including CS grads.
Some things you will never need to know.
imposter-syndrome  computer-science  system-of-professions  careering  worklife  self-definition  to-write-about 
27 days ago
Navigating with grid-like representations in artificial agents | DeepMind
Most animals, including humans, are able to flexibly navigate the world they live in – exploring new areas, returning quickly to remembered places, and taking shortcuts. Indeed, these abilities feel so easy and natural that it is not immediately obvious how complex the underlying processes really are. In contrast, spatial navigation remains a substantial challenge for artificial agents whose abilities are far outstripped by those of mammals.
ethology  experiment  artificial-life  neural-networks  to-write-about  consider:nudge  consider:pattern-libraries 
27 days ago
The Only Woman to Win the Nobel Prize in Economics Also Debunked the Orthodoxy - Evonomics
I mention Lloyd’s essay to illustrate how ridiculous yet persistent the misconceptions about the “tragedy” dynamic truly are. Commons scholar Lewis Hyde dryly notes, “Just as Hardin proposes a herdsman whose reason is unable to encompass the common good, so Lloyd supposes persons who have no way to speak with each other or make joint decisions. Both writers inject laissez-faire individualism into an old agrarian village and then gravely announce that the commons is dead. From the point of view of such a village, Lloyd’s assumptions are as crazy as asking us to ‘suppose a man to have a purse to which his left and right hand may freely resort, each unaware of the other’.”

This absurdity, unfortunately, is the basis for a large literature of “prisoner’s dilemma” experiments that purport to show how “rational individuals” behave when confronted with “social dilemmas,” such as how to allocate a limited resource. Should the “prisoner” cooperate with other potential claimants and share the limited rewards? Or should he or she defect by grabbing as much for himself as possible?
economics  ideology  public-policy  models-and-modes  commons  to-write-about  theory-and-practice-sitting-in-a-tree  libertarianism  assumptions 
5 weeks ago
[1804.05445] Evolving Event-driven Programs with SignalGP
We present SignalGP, a new genetic programming (GP) technique designed to incorporate the event-driven programming paradigm into computational evolution's toolbox. Event-driven programming is a software design philosophy that simplifies the development of reactive programs by automatically triggering program modules (event-handlers) in response to external events, such as signals from the environment or messages from other programs. SignalGP incorporates these concepts by extending existing tag-based referencing techniques into an event-driven context. Both events and functions are labeled with evolvable tags; when an event occurs, the function with the closest matching tag is triggered. In this work, we apply SignalGP in the context of linear GP. We demonstrate the value of the event-driven paradigm using two distinct test problems (an environment coordination problem and a distributed leader election problem) by comparing SignalGP to variants that are otherwise identical, but must actively use sensors to process events or messages. In each of these problems, rapid interaction with the environment or other agents is critical for maximizing fitness. We also discuss ways in which SignalGP can be generalized beyond our linear GP implementation.
gptp  hey-I-know-this-guy  genetic-programming  representation  to-write-about 
5 weeks ago
[1802.03676] Differentiable Dynamic Programming for Structured Prediction and Attention
Dynamic programming (DP) solves a variety of structured combinatorial problems by iteratively breaking them down into smaller subproblems. In spite of their versatility, DP algorithms are usually non-differentiable, which hampers their use as a layer in neural networks trained by backpropagation. To address this issue, we propose to smooth the max operator in the dynamic programming recursion, using a strongly convex regularizer. This allows to relax both the optimal value and solution of the original combinatorial problem, and turns a broad class of DP algorithms into differentiable operators. Theoretically, we provide a new probabilistic perspective on backpropagating through these DP operators, and relate them to inference in graphical models. We derive two particular instantiations of our framework, a smoothed Viterbi algorithm for sequence prediction and a smoothed DTW algorithm for time-series alignment. We showcase these instantiations on two structured prediction tasks and on structured and sparse attention for neural machine translation.
representation  time-series  numerical-methods  deep-learning  rather-interesting  nudge-targets  consider:representation 
5 weeks ago
[1803.05859v3] Neural Network Quine
Self-replication is a key aspect of biological life that has been largely overlooked in Artificial Intelligence systems. Here we describe how to build and train self-replicating neural networks. The network replicates itself by learning to output its own weights. The network is designed using a loss function that can be optimized with either gradient-based or non-gradient-based methods. We also describe a method we call regeneration to train the network without explicit optimization, by injecting the network with predictions of its own parameters. The best solution for a self-replicating network was found by alternating between regeneration and optimization steps. Finally, we describe a design for a self-replicating neural network that can solve an auxiliary task such as MNIST image classification. We observe that there is a trade-off between the network's ability to classify images and its ability to replicate, but training is biased towards increasing its specialization at image classification at the expense of replication. This is analogous to the trade-off between reproduction and other tasks observed in nature. We suggest that a self-replication mechanism for artificial intelligence is useful because it introduces the possibility of continual improvement through natural selection.
artificial-life  machine-learning  quines  rather-interesting  to-write-about  hey-I-know-this-guy 
5 weeks ago
DAVID GRAEBER / The Revolt of the Caring Classes / 2018 - YouTube
"The financialisation of major economies since the '80s has radically changed the terms for social movements everywhere. How does one organise workplaces, for example, in societies where up to 40% of the workforce believe their jobs should not exist? David Graeber makes the case that, slowly but surely, a new form of class politics is emerging, based around recognising the centrality of meaningful 'caring labour' in creating social value. He identifies a slowly emerging rebellion of the caring classes which potentially represents just as much of a threat to financial capitalism as earlier forms of proletarian struggle did to industrial capitalism.

David Graeber is Professor of Anthropology, London School of Economics and previously Assistant Professor and Associate Professor of Anthropology at Yale and Reader in Social Anthropology at Goldsmiths, University of London. His books include The Utopia of Rules: On Technology, Stupidity, and the Secret Joys of Bureaucracy (2015) Debt: The First 5000 Years (2011) and Fragments of an Anarchist Anthropology (2004). His activism includes protests against the 3rd Summit of the Americas in Quebec City in 2001, and the 2002 World Economic Forum in New York City. Graeber was a leading figure in the Occupy Wall Street movement, and is sometimes credited with having coined the slogan, 'We are the 99 percent'.

This lecture was given at the Collège de France on the 22nd March 2018."
have-watched  very-good  care  caring  teaching  nursing  economics  capitalism  labor  work  employment  compensation  resentment  bullshitjobs  finance  politics  policy  us  uk  workingclass  intellectuals  intellectualism  society  manufacturing  management  jobs  liberalism  values  benefits  nobility  truth  beauty  charity  nonprofit  highered  highereducation  activism  humanrights  os  occupywallstreet  opportunity  revolution  revolt  hollywood  military  misery  productivity  creation  creativity  maintenance  gender  production  reproduction  socialsciences  proletariat  wagelabor  wage  salaries  religion  belief  discipline  maintstreamleft  hospitals  freedom  play  teachers  parenting  mothers  education  learning  unions  consumption  anarchism  spontaneity  universalbasicincome  via:robertogreco 
5 weeks ago
[1801.07155] Continued fractions and orderings on the Markov numbers
Markov numbers are integers that appear in the solution triples of the Diophantine equation, x2+y2+z2=3xyz, called the Markov equation. A classical topic in number theory, these numbers are related to many areas of mathematics such as combinatorics, hyperbolic geometry, approximation theory and cluster algebras.
There is a natural map from the rational numbers between zero and one to the Markov numbers. In this paper, we prove two conjectures seen in Martin Aigner's book, Markov's theorem and 100 years of the uniqueness conjecture, that determine an ordering on subsets of the Markov numbers based on their corresponding rational.
The proof uses the cluster algebra of the torus with one puncture and a resulting reformulation of the conjectures in terms of continued fractions. The key step is to analyze the difference in the numerator of a continued fraction when an operation is applied to its entries.
number-theory  continued-fractions  rather-interesting  to-write-about  consider:looking-to-see  consider:generalizations 
6 weeks ago
[1803.08823] A high-bias, low-variance introduction to Machine Learning for physicists
Machine Learning (ML) is one of the most exciting and dynamic areas of modern research and application. The purpose of this review is to provide an introduction to the core concepts and tools of machine learning in a manner easily understood and intuitive to physicists. The review begins by covering fundamental concepts in ML and modern statistics such as the bias-variance tradeoff, overfitting, regularization, and generalization before moving on to more advanced topics in both supervised and unsupervised learning. Topics covered in the review include ensemble models, deep learning and neural networks, clustering and data visualization, energy-based models (including MaxEnt models and Restricted Boltzmann Machines), and variational methods. Throughout, we emphasize the many natural connections between ML and statistical physics. A notable aspect of the review is the use of Python notebooks to introduce modern ML/statistical packages to readers using physics-inspired datasets (the Ising Model and Monte-Carlo simulations of supersymmetric decays of proton-proton collisions). We conclude with an extended outlook discussing possible uses of machine learning for furthering our understanding of the physical world as well as open problems in ML where physicists maybe able to contribute. (Notebooks are available at this https URL )
rather-interesting  machine-learning  text  review 
6 weeks ago
Agility should pay attention to Sociology – Romeu Moura – Medium
So I wrote myself a thread to explain 3 concepts from Bourdieu and their impact in Agility
sociology  agility  rather-good  to-write-about 
6 weeks ago
The Artist Who Drew With Computers, Before Computers Were a Thing - SURFACE
“What makes Molnár’s work so important today is that her ability to experiment was aided and amplified by the tools she used,” say Anderson and Bianconi. “This spirit of experimentation allowed these works to be both systematic and humanistic, and has been influential for artists who have worked with computers since.”
generative-art  art-criticism  history  to-write-about  exhibition 
6 weeks ago
The Metonymy of Matrices - Scientific American Blog Network
As a tool, the matrix is so powerful that it is easy to forget that it is a representation of a function, not a function itself. A matrix truly is just the array of numbers, but I think in this context, most mathematicians are metonymists. (Metonymers? Metonymnistes?) We think of the matrix as the function itself, and it’s easy to lose sight of the fact that it's only notation. Matrices don’t even have to encode linear transformations. They are used in other contexts in mathematics, too, and restricting our definition to linear transformations can shortchange the other applications (though for my money, the value of the matrix as a way of representing linear transformations dwarfs any other use they have).
matrices  representation  functions  mathematical-recreations  to-write-about 
6 weeks ago
The Job Guarantee and the Wilted Liberal Imagination : Democracy Journal
"You can’t say this kind of public work and employment is impossible if you’re living in a society built by it."
economics  public-policy  labor  history-is-a-feature-not-a-bug 
6 weeks ago
Orthogonal polygons | The Math Less Traveled
Quite a few commenters figured out what was going on, and mentioned several nice (equivalent) ways to think about it. Primarily, the idea is to draw all possible orthogonal polygons, that is, polygons with only right angles, organized by the total number of vertices. (So, for example, the picture above shows all orthogonal polygons with exactly ten vertices.) However, we have to be careful what we mean by the phrase “all possible”: there would be an infinite number of such polygons if we think about things like the precise lengths of edges. So we have to say when two polygons are considered the same, and when they are distinct. My rules are as follows:
mathematical-recreations  looking-to-see  geometry  polyominoes  to-write-about 
7 weeks ago
Cooking the books – Almost looks like work
Since Christmas, at my house we’ve been cooking with 5 ingredients or fewer thanks to the acquisition of Jamie Oliver’s new book, the contents of which are mostly available online here. The recipes are unanimously very tasty, but that’s besides the point. The real mark of culinary excellence (in my humble opinion) is how efficiently one can buy ingredients to make as many of the recipes as possible in one shopping trip. Let’s investigate while the lamb is on.


Each of the 135 recipes in the book consists of 5 ingredients, some of which overlap. It is therefore not necessary to purchase 675 ingredients, there are actually only 239 unique ones. (Yes, I did spend a Sunday morning typing 675 individual ingredients into a spreadsheet.)

The question is then this:

In which order should I buy my ingredients to maximise the number of possible recipes as a function of number of ingredients?

Let’s start simply, and look at the frequency of occurrence of the ingredients.
mathematical-recreations  looking-to-see  cooking  data-analysis  leading-questions  rather-interesting 
7 weeks ago
Props in Network Theory | Azimuth
We start with circuits made solely of ideal perfectly conductive wires. Then we consider circuits with passive linear components like resistors, capacitors and inductors. Finally we turn on the power and consider circuits that also have voltage and current sources.

And here’s the cool part: each kind of circuit corresponds to a prop that pure mathematicians would eventually invent on their own! So, what’s good for engineers is often mathematically natural too.
network-theory  abstraction  rather-interesting  models-and-modes  circles-and-arrows  bond-diagrams  to-write-about  to-understand  functional-programming  category-theory 
7 weeks ago
Solved: A Decades-Old Ansel Adams Mystery - Atlas Obscura
WHEN YOU LOOK AT THE image above, what do you think of? Most will probably take in the beauty of its subjects, the mountain Denali and nearby Wonder Lake. A photographer might admire the skill of its creator, Ansel Adams. Adventurers may feel the urge to climb.

Donald Olson sees all that and something else: a mystery. He wants to know the moment it was taken. An astrophysicist and forensic astronomer, Olson uses quantitative methods to answer questions raised by artwork, literature, and historical accounts—not the heady ones, but the basic, surprisingly slippery who, what, when, and where.
photography  art-history  rather-interesting  inverse-problems  astronomy  via:kottke.org 
7 weeks ago
Generating function - Wikipedia
In mathematics, a generating function is a way of encoding an infinite sequence of numbers (an) by treating them as the coefficients of a power series. The sum of this infinite series is the generating function. Unlike an ordinary series, this formal series is allowed to diverge, meaning that the generating function is not always a true function and the "variable" is actually an indeterminate. Generating functions were first introduced by Abraham de Moivre in 1730, in order to solve the general linear recurrence problem.[1] One can generalize to formal series in more than one indeterminate, to encode information about arrays of numbers indexed by several natural numbers.
There are various types of generating functions, including ordinary generating functions, exponential generating functions, Lambert series, Bell series, and Dirichlet series; definitions and examples are given below. Every sequence in principle has a generating function of each type (except that Lambert and Dirichlet series require indices to start at 1 rather than 0), but the ease with which they can be handled may differ considerably. The particular generating function, if any, that is most useful in a given context will depend upon the nature of the sequence and the details of the problem being addressed.
Generating functions are often expressed in closed form (rather than as a series), by some expression involving operations defined for formal series. These expressions in terms of the indeterminate x may involve arithmetic operations, differentiation with respect to x and composition with (i.e., substitution into) other generating functions; since these operations are also defined for functions, the result looks like a function of x. Indeed, the closed form expression can often be interpreted as a function that can be evaluated at (sufficiently small) concrete values of x, and which has the formal series as its series expansion; this explains the designation "generating functions". However such interpretation is not required to be possible, because formal series are not required to give a convergent series when a nonzero numeric value is substituted for x. Also, not all expressions that are meaningful as functions of x are meaningful as expressions designating formal series; for example, negative and fractional powers of x are examples of functions that do not have a corresponding formal power series.
Generating functions are not functions in the formal sense of a mapping from a domain to a codomain. Generating functions are sometimes called generating series,[2] in that a series of terms can be said to be the generator of its sequence of term coefficients.
mathematics  via:arthegall  to-understand  rather-interesting  to-write-about  nudge-targets  hmmmmmm 
8 weeks ago
McGee Graph | Visual Insight
The Heawood and Tutte–Coxeter graphs are Levi graphs. In other words, they arise from a finite configuration of points and lines, with each vertex corresponding to either a point or line, and an edge connecting two vertices whenever we have a point lying on a line. The McGee graph cannot be a Levi graph, because it is not bipartite. In other words, it doesn’t admit a 2-coloring of its vertices, where the edges only connect vertices of one color to vertices of the other color. The picture above shows a 3-coloring of the McGee graph.
graph-theory  geometry  rather-interesting  to-write-about  nudge-targets 
8 weeks ago
Complexity Explorer
New for 2018, our flagship course, Introduction to Complexity, will be open year round. All units will be available at all times, so you can learn the fundamentals of Complex Systems Science at your own pace, and earn your certificate at any time. 

All other courses are designed to be similar to a semester-long course, offering the chance to delve into a subject deeply. Courses are available in two ways: as a course session, or an archived course.  Each course is usually offered in one session per calendar year.

Tutorials are short, self-paced “mini-courses” designed to introduce students to important techniques and to provide illustrations of their application in complex systems.

Complexity Explorer's courses and tutorials are supported by user donations and contributions from the Santa Fe Institute.  Please consider donating to support further course and tutorial development.
MOOC  complexology  hey-I-know-this-guy  to-watch  to-write-about 
8 weeks ago
Scientists Still Can't Decide How to Define a Tree - The Atlantic
If one is pressed to describe what makes a tree a tree, long life is right up there with wood and height. While many plants have a predictably limited life span (what scientists call programmed senescence), trees don’t, and many persist for centuries. In fact, that trait—indefinite growth—could be science’s tidiest demarcation of tree-ness, even more than woodiness. Yet it’s only helpful to a point. We think we know what trees are, but they slip through the fingers when we try to define them.
biology  define-your-terms  rather-interesting  taxonomy  philosophy-of-science 
8 weeks ago
Homotopy type theory - Wikipedia
In mathematical logic and computer science, homotopy type theory (HoTT /hɒt/) refers to various lines of development of intensional type theory, based on the interpretation of types as objects to which the intuition of (abstract) homotopy theory applies.
This includes, among other lines of work, the construction of homotopical and higher-categorical models for such type theories; the use of type theory as a logic (or internal language) for abstract homotopy theory and higher category theory; the development of mathematics within a type-theoretic foundation (including both previously existing mathematics and new mathematics that homotopical types make possible); and the formalization of each of these in computer proof assistants.
There is a large overlap between the work referred to as homotopy type theory, and as the univalent foundations project. Although neither is precisely delineated, and the terms are sometimes used interchangeably, the choice of usage also sometimes corresponds to differences in viewpoint and emphasis.[1] As such, this article may not represent the views of all researchers in the fields equally.
mathematics  recommended-by-barista  to-understand  abstruse  possibly-interesting 
8 weeks ago
killcord
Killcord is a tool used to build resilient deadman's switches for releasing encrypted payloads. In its default configuration, killcord leverages ethereum and ipfs for censorship resistance. The killcord project owner hides a secret key from the world by checking in to the killcord smart contract on ethereum. If the owner stops checking in after a period of time, the killcord is triggered and the secret key that decrypts an encrypted payload is published.
for-a-project  privacy  security  software 
8 weeks ago
Sturgeon’s Biases – Quietstars – Medium
Some smart social psychologist, anthropologist or sociologist probably wrote about this seventy years ago. So I’m just going to ramble about it here for a bit, and hope that somebody smarter than I am can point me to that paper. So I know what to call it.
communities-of-practice  cultural-assumptions  cultural-norms  essay  social-norms  rather-interesting 
9 weeks ago
[1804.01622] Image Generation from Scene Graphs
To truly understand the visual world our models should be able not only to recognize images but also generate them. To this end, there has been exciting recent progress on generating images from natural language descriptions. These methods give stunning results on limited domains such as descriptions of birds or flowers, but struggle to faithfully reproduce complex sentences with many objects and relationships. To overcome this limitation we propose a method for generating images from scene graphs, enabling explicitly reasoning about objects and their relationships. Our model uses graph convolution to process input graphs, computes a scene layout by predicting bounding boxes and segmentation masks for objects, and converts the layout to an image with a cascaded refinement network. The network is trained adversarially against a pair of discriminators to ensure realistic outputs. We validate our approach on Visual Genome and COCO-Stuff, where qualitative results, ablations, and user studies demonstrate our method's ability to generate complex images with multiple objects.
deep-learning  image-processing  generative-art  generative-models  turning-the-handle-the-other-way  to-write-about  to-do 
9 weeks ago
Exactly how bad is the 13 times table? | The Aperiodical
Along the way, OEIS editor Charles R Greathouse IV added this intriguing conjecture:

Conjecture: a(n)≤N
for all n
. Perhaps N
can be taken as 81
.
number-theory  mathematical-recreations  open-questions  to-write-about  consider:feature-discovery 
9 weeks ago
Letting neural networks be weird
Machine learning algorithms are not like other computer programs. In the usual sort of programming, a human programmer tells the computer exactly what to do. In machine learning, the human programmer merely gives the algorithm the problem to be solved, and through trial-and-error the algorithm has to figure out how to solve it.

This often works really well - machine learning algorithms are widely used for facial recognition, language translation, financial modeling, image recognition, and ad delivery. If you’ve been online today, you’ve probably interacted with a machine learning algorithm.
machine-learning  noteworthy  to-invite-to-GPTP 
9 weeks ago
How 'Deaf President Now' Changed America - Pacific Standard
The lessons from Deaf President Now should be clear. Its success, fueled by direct action, shows that rights have to be claimed rather than given. Deaf President Now stands as a watershed moment in the history not just of Deaf and disability rights, but also of American civil rights more broadly. As I spoke to people who had been instrumental in the protests, and the current president of Gallaudet, I heard one additional message: a fear that too few Americans even remember this story.
civil-rights  protest  public-policy  collective-action  activism 
9 weeks ago
Laudator Temporis Acti: The Poligs of the Oern Vent
'The Poligs of the Oern Vent in dugard to the Brounincinl Coutrick is the colic of the unscrifulouse Gawler.' So ran the printed slip technically known as a 'rough proof'. The Aryan had surpassed himself; but, as he read, light filled the mind of the Reader. He had written — 'The policy of the Government in regard to the Provincial Contract is the policy of the unscrupulous lawyer', and, behold, with a mere turn of his wrist, the Aryan had glorified, and enriched with the wealth of an exuberant Orientalism that simple sentence, till it stood forth a gem, or rather a collection of gems! 'The Poligs of the Oern Vent' — George Meredith might have woven those words into the Shaving of Shagpat, and so made that dazzling piece of broidery yet more gorgeous. 'Brounincinl Coutrick' would suit admirably the manager of a travelling-circus. Conceive the effect, on white and red posters of: — 'To-night! To-night!! To-night!!! The Brounincinl Coutrick!' The words would draw thousands — millions. 'Unscrifulouse Gawler' again would furnish an absolutely unique and startling title for a semi-humourous, semi-grotesque, wholly-horrible story, of the American school, let us say. Think for a moment what fashion of ghoulo-demoniacal, triple-Quilpian, Jekyll-and-Hydeous character, the 'unscrifulouse Gawler' would be. Out of the incult wantonings of a Punjabi Mahommedan with a box of type, had been born the suggestions of three Brilliant Notions, did any man care to use them, exactly as ideas for patterns are conveyed to the designer by the chance-ruled twists of the Kaleidescope.
nanohistory  generative-art  inspiration  unexpected-similarities  Lewis-Carroll  seek-ye-the-original 
10 weeks ago
Myth & Moor: The Wild Time of the Sickbed
Yet the loss is not really of time itself, but of one particular form of it: the "productive" time prized in our commerical culture, which priviliges results and finished products over process. "Time is money," as the old saying goes, and a sick person's time is not worth a bad penny. Yet paradoxically, when we're in poor health we are often rich in time, but in the wrong kind of time: the "unproductive" time of the sickbed. After a lifetime lived in the liminal space between disability and good health, I have come to believe "unproductive" time has its place and its value as well.
art  creativity  essay 
10 weeks ago
mathrecreation: Tigers and Treasure
The graph below shows all 196 possible puzzles. The puzzles that lead to contradictions are coloured as white squares, the puzzles that do not lead to contradictions are coloured in black. We can see a white strip across the bottom: these are all the puzzles where door 2 is labelled with statement 1. Can you find the statement that always leads to contradictions for door 1? There are 131 puzzles that are "good" in the sense that they do not lead to contradictions.
mathematical-recreations  logic  looking-to-see  to-write-about  consider:robustness  nudge-targets 
10 weeks ago
[1803.01422] DAGs with NO TEARS: Smooth Optimization for Structure Learning
Estimating the structure of directed acyclic graphs (DAGs, also known as Bayesian networks) is a challenging problem since the search space of DAGs is combinatorial and scales superexponentially with the number of nodes. Existing approaches rely on various local heuristics for enforcing the acyclicity constraint and are not well-suited to general purpose optimization packages for their solution. In this paper, we introduce a fundamentally different strategy: We formulate the structure learning problem as a smooth, constrained optimization problem over real matrices that avoids this combinatorial constraint entirely. This is achieved by a novel characterization of acyclicity that is not only smooth but also exact. The resulting nonconvex, constrained program involves smooth functions whose gradients are easy to compute and only involve elementary matrix operations. By using existing black-box optimization routines, our method uses global search to find an optimal DAG and can be implemented in about 50 lines of Python and outperforms existing methods without imposing any structural constraints.
graph-theory  combinatorics  algorithms  rather-interesting  computational-complexity  to-understand  to-write-about  nudge-targets  consider:looking-to-see  representation 
11 weeks ago
The Woman Who Bested the Men at Math | History | Smithsonian
To be a woman in the Victorian age was to be weak: the connection was that definite. To be female was also to be fragile, dependent, prone to nerves and—not least—possessed of a mind that was several degrees inferior to a man’s. For much of the 19th century, women were not expected to shine either academically or athletically, and those who attempted to do so were cautioned that they were taking an appalling risk. Mainstream medicine was clear on this point: to dream of studying at the university level was to chance madness or sterility, if not both.

It took generations to transform this received opinion; that, a long series of scientific studies, and the determination and hard work of many thousands of women. For all that, though, it is still possible to point to one single achievement, and one single day, and say: this is when everything began to change. That day was June 7, 1890, when—for the first and only time—a woman ranked first in the mathematical examinations held at the University of Cambridge. It was the day that Philippa Fawcett placed “above the Senior Wrangler.”
nanohistory  sexism  biography  mathematics  academic-culture 
11 weeks ago
History Dependent Cellular Automata | Softology's Blog
I have been exploring a variety of cellular automata lately and here is another one.

This is from another idea I had. Andrew Adamatzky let me know there has been work done using previous states before referred to as “Cellular Automata with Memory”. See these papers by Ramon Alonso-Sanz for other examples of 1D and 2D CAs using memory from previous generations.

This is a totalistic CA that uses the usual 8 immediate neighbor cells as well as the last step’s current cell and 8 neighbors. This gives a total of 17 neighbor cells that can influence the birth and survival of the cells.

I call them “History Dependent Cellular Automata” because they depend on the previous cycles’ neighbor cells as well as the usual 8 immediate neighbor cells.
cellular-automata  generative-art  to-write-about 
11 weeks ago
Context Free Art
Context Free is a program that generates images from written instructions called a grammar. The program follows the instructions in a few seconds to create images that can contain millions of shapes.
generative-art  rather-interesting  graphics  programming-language  to-understand 
11 weeks ago
[1804.00222] Learning Unsupervised Learning Rules
A major goal of unsupervised learning is to discover data representations that are useful for subsequent tasks, without access to supervised labels during training. Typically, this goal is approached by minimizing a surrogate objective, such as the negative log likelihood of a generative model, with the hope that representations useful for subsequent tasks will arise as a side effect. In this work, we propose instead to directly target a later desired task by meta-learning an unsupervised learning rule, which leads to representations useful for that task. Here, our desired task (meta-objective) is the performance of the representation on semi-supervised classification, and we meta-learn an algorithm -- an unsupervised weight update rule -- that produces representations that perform well under this meta-objective. Additionally, we constrain our unsupervised update rule to a be a biologically-motivated, neuron-local function, which enables it to generalize to novel neural network architectures. We show that the meta-learned update rule produces useful features and sometimes outperforms existing unsupervised learning techniques. We show that the meta-learned unsupervised update rule generalizes to train networks with different widths, depths, and nonlinearities. It also generalizes to train on data with randomly permuted input dimensions and even generalizes from image datasets to a text task.
machine-learning  unsupervised-learning  rather-interesting  feature-extraction  clustering  algorithms  to-write-about 
11 weeks ago
[1803.05316] Seven Sketches in Compositionality: An Invitation to Applied Category Theory
This book is an invitation to discover advanced topics in category theory through concrete, real-world examples. It aims to give a tour: a gentle, quick introduction to guide later exploration. The tour takes place over seven sketches, each pairing an evocative application, such as databases, electric circuits, or dynamical systems, with the exploration of a categorical structure, such as adjoint functors, enriched categories, or toposes.
No prior knowledge of category theory is assumed.
category-theory  book  to-read  to-write-about  via:several  rather-interesting 
11 weeks ago
[1802.01396] To understand deep learning we need to understand kernel learning
Generalization performance of classifiers in deep learning has recently become a subject of intense study. Heavily over-parametrized deep models tend to fit training data exactly. Despite overfitting, they perform well on test data, a phenomenon not yet fully understood.
The first point of our paper is that strong performance of overfitted classifiers is not a unique feature of deep learning. Using real-world and synthetic datasets, we establish that kernel classifiers trained to have zero classification error (overfitting) or even zero regression error (interpolation) perform very well on test data.
We proceed to prove lower bounds on the norm of overfitted solutions for smooth kernels, showing that they increase nearly exponentially with the data size. Since most generalization bounds depend polynomially on the norm of the solution, this result implies that they diverge as data increases. Furthermore, the existing bounds do not apply to interpolated classifiers.
We also show experimentally that (non-smooth) Laplacian kernels easily fit random labels using a version of SGD, a finding that parallels results reported for ReLU neural networks. In contrast, fitting noisy data requires many more epochs for smooth Gaussian kernels. The observation that the performance of overfitted Laplacian and Gaussian classifiers on the test is quite similar, suggests that generalization is tied to the properties of the kernel function rather than the optimization process.
We see that some key phenomena of deep learning are manifested similarly in kernel methods in the overfitted regime. We argue that progress on understanding deep learning will be difficult, until more analytically tractable "shallow" kernel methods are better understood. The experimental and theoretical results presented in this paper indicate a need for new theoretical ideas for understanding classical kernel methods.
machine-learning  philosophy-of-engineering  looking-to-see  statistics  algorithms  explanation  to-write-about  explanatory-power-and-narrative-discovery 
11 weeks ago
The moving sofa problem — Dan Romik's home page
The mathematician Leo Moser posed in 1966 the following curious mathematical problem: what is the shape of largest area in the plane that can be moved around a right-angled corner in a two-dimensional hallway of width 1? This question became known as the moving sofa problem, and is still unsolved fifty years after it was first asked.
mathematical-recreations  computational-geometry  engineering-design  constraint-satisfaction  rather-interesting  nudge-targets  to-write-about 
11 weeks ago
Image analysis driven single-cell analytics for systems microbiology | BMC Systems Biology | Full Text
BaSCA can be used to analyze accurately and efficiently cell movies both at a high resolution (single-cell level) and at a large scale (communities with many dense colonies) as needed to shed light on e.g. how bacterial community effects and epigenetic information transfer play a role on important phenomena for human health, such as biofilm formation, persisters’ emergence etc. Moreover, it enables studying the role of single-cell stochasticity without losing sight of community effects that may drive it.
machine-learning  image-processing  image-segmentation  cell-biology  indistinguishable-from-magic  experimental-biology  wow  algorithms 
11 weeks ago
ties and insight | sara hendren
Carson’s father died in 1935, followed, two years later, by her older sister, leaving Carson to care for her mother and her nieces, ages eleven and twelve; she later adopted her grandnephew, when he was orphaned at the age of four. These obligations sometimes frustrated Carson, but not half as much as they frustrate her biographers. For [these biographers], Carson’s familial obligations—in particular, the children—are nothing but burdens that “deprived her of privacy and drained her physical and emotional energy.” They mean this generously, as a way of accounting for why Carson didn’t write more, and why, except for her Sun articles, she never once submitted a manuscript on time.But caring for other people brings its own knowledge. Carson came to see the world as beautiful, wild, animal, and vulnerable, each part attached to every other part, not only through prodigious scientific research but also through a lifetime of caring for the very old and the very young, wiping a dying man’s brow, tucking motherless girls into bed, heating up dinners for a lonely little boy. The domestic pervades Carson’s understanding of nature. “Wildlife, it is pointed out, is dwindling because its home is being destroyed,” she wrote in 1938, “but the home of the wildlife is also our home.” If she’d had fewer ties, she would have had less insight.
insight  aging  caregiving  lovely  nanohistory  biography 
11 weeks ago
Biomimetics | Free Full-Text | A Parallel Modular Biomimetic Cilia Sorting Platform
The aquatic unicellular organism Paramecium caudatum uses cilia to swim around its environment and to graze on food particles and bacteria. Paramecia use waves of ciliary beating for locomotion, intake of food particles and sensing. There is some evidence that Paramecia pre-sort food particles by discarding larger particles, but intake the particles matching their mouth cavity. Most prior attempts to mimic cilia-based manipulation merely mimicked the overall action rather than the beating of cilia. The majority of massive-parallel actuators are controlled by a central computer; however, a distributed control would be far more true-to-life. We propose and test a distributed parallel cilia platform where each actuating unit is autonomous, yet exchanging information with its closest neighboring units. The units are arranged in a hexagonal array. Each unit is a tileable circuit board, with a microprocessor, color-based object sensor and servo-actuated biomimetic cilia actuator. Localized synchronous communication between cilia allowed for the emergence of coordinated action, moving different colored objects together. The coordinated beating action was capable of moving objects up to 4 cm/s at its highest beating frequency; however, objects were moved at a speed proportional to the beat frequency. Using the local communication, we were able to detect the shape of objects and rotating an object using edge detection was performed; however, lateral manipulation using shape information was unsuccessful. View Full-Text
biological-engineering  microbiology  nanotechnology  rather-interesting  to-write-about  sorting  emergent-design 
11 weeks ago
Three representations of the Ising model | Scientific Reports
Statistical models that analyse (pairwise) relations between variables encompass assumptions about the underlying mechanism that generated the associations in the observed data. In the present paper we demonstrate that three Ising model representations exist that, although each proposes a distinct theoretical explanation for the observed associations, are mathematically equivalent. This equivalence allows the researcher to interpret the results of one model in three different ways. We illustrate the ramifications of this by discussing concepts that are conceived as problematic in their traditional explanation, yet when interpreted in the context of another explanation make immediate sense.
representation  modeling  philosophy-of-science  rather-interesting  to-write-about  demonstrations-of-the-mangle 
11 weeks ago
A Review of Perl 6 – Evan Miller
In case you missed it, and I think everyone did, Perl 6 was released to the world a year and a half ago — on Christmas of 2015, incidentally — after an effort nominally spanning almost sixteen years. (I think, but am not certain, my uncle’s dissertation was also completed at some point.) The market for new programming languages, as I write this in 2017, is competitive but not impenetrable — but like a freshly minted Ph.D., no one seems to be sure of Perl 6’s market prospects, and like a just-turned-in dissertation, no one seems to know whether the fruit of many years’ labor is actually worth a damn.
perl  programming-language  engineering-criticism  review  rather-interesting 
11 weeks ago
Robot Skill Learning: From Reinforcement Learning to Evolution Strategies : Paladyn, Journal of Behavioral Robotics
Policy improvement methods seek to optimize the parameters of a policy with respect to a utility function. Owing to current trends involving searching in parameter space (rather than action space) and using reward-weighted averaging (rather than gradient estimation), reinforcement learning algorithms for policy improvement, e.g. PoWER and PI2, are now able to learn sophisticated high-dimensional robot skills. A side-effect of these trends has been that, over the last 15 years, reinforcement learning (RL) algorithms have become more and more similar to evolution strategies such as (μW , λ)-ES and CMA-ES. Evolution strategies treat policy improvement as a black-box optimization problem, and thus do not leverage the problem structure, whereas RL algorithms do. In this paper, we demonstrate how two straightforward simplifications to the state-of-the-art RL algorithm PI2 suffice to convert it into the black-box optimization algorithm (μW, λ)-ES. Furthermore, we show that (μW , λ)-ES empirically outperforms PI2 on the tasks in [36]. It is striking that PI2 and (μW , λ)-ES share a common core, and that the simpler algorithm converges faster and leads to similar or lower final costs. We argue that this difference is due to a third trend in robot skill learning: the predominant use of dynamic movement primitives (DMPs). We show how DMPs dramatically simplify the learning problem, and discuss the implications of this for past and future work on policy improvement for robot skill learning
robotics  machine-learning  metaheuristics  algorithms  learning-by-doing  engineering-design  planning  to-write-about 
11 weeks ago
The meaning of model equivalence: Network models, latent variables, and the theoretical space in between | Psych Networks
Recently, an important set of equivalent representations of the Ising model was published by Joost Kruis and Gunter Maris in Scientific Reports. The paper constructs elegant representations of the Ising model probability distribution in terms of a network model (which consists of direct relations between observables), a latent variable model (which consists of relations between a latent variable and observables, in which the latent variable acts as a common cause), and a common effect model (which also consists of relations between a latent variable and observables, but here the latent variable acts as a common effect). The latter equivalence is a novel contribution to the literature and a quite surprising finding, because it means that a formative model can be statistically equivalent to a reflective model, which one may not immediately expect (do note that this equivalence need not maintain dimensionality, so a model with a single common effect may translate in a higher-dimensional latent variable model).

However, the equivalence between the ordinary (reflective) latent variable models and network models has been with us for a long time, and I therefore was rather surprised at some people’s reaction to the paper and the blog post that accompanies it. Namely, it appears that some think that (a) the fact that network structures can mimic reflective latent variables and vice versa is a recent discovery, that (b) somehow spells trouble for the network approach itself (because, well, what’s the difference?). The first of these claims is sufficiently wrong to go through the trouble of refuting it, if only to set straight the historical record; the second is sufficiently interesting to investigate it a little more deeply. Hence the following notes.
dynamical-systems  models  models-and-modes  representation  philosophy-of-science  (in-practice)  to-write-about  via:several 
11 weeks ago
"Brahmin Left vs Merchant Right" (PDF)
Abstract. Using post-electoral surveys from France, Britain and the US, this paper documents a striking long-run evolution in the structure of political cleavages. In the 1950s-1960s, the vote for left-wing (socialist-labour-democratic) parties was associated with lower education and lower income voters. It has gradually become associated with higher education voters, giving rise to a “multiple-elite” party system in the 2000s-2010s: high-education elites now vote for the “left”, while high- income/high-wealth elites still vote for the “right” (though less and less so). I argue that this can contribute to explain rising inequality and the lack of democratic response to it, as well as the rise of “populism”. I also discuss the origins of this evolution (rise of globalization/migration cleavage, and/or educational expansion per se) as well as future prospects: “multiple-elite” stabilization; complete realignment of the party system along a “globalists” (high-education, high-income) vs “nativists” (low- education, low-income) cleavage; return to class-based redistributive conflict (either from an internationalist or nativist perspective). Two main lessons emerge. First, with multi-dimensional inequality, multiple political equilibria and bifurcations can occur. Next, without a strong egalitarian-internationalist platform, it is difficult to unite low- education, low-income voters from all origins within the same party.
via:several  inequality  sociology  economics  political-economy  cultural-dynamics  cultural-norms 
11 weeks ago
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