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FontCode
RT : encode information in text documents ... like the idea
glyph  steganography  perturbation  from twitter
may 2018 by lijnenspel
prosthetic knowledge — FontCode Research from Columbia Computer Graphics...
Using font kerning as a form of steganography, very subtle, but with high rez pictures, can you run the reverse, checking against known fonts to detect possible steg usage, or do you have to allow for enough slop in printing and camera angle that you would get too many false positives?
FontCode  encryption  cryptography  steganography  fingerprinting  font  kerning  glyph  perturbation 
april 2018 by asteroza
The upside of London Tube strikes
Making use of the considerable variation in the degree of distortion represented in the Tube map across different parts of London (something that is unobserved to most commuters), our results suggest that those who live in (or travel to) more distorted areas were less likely to return to their pre-strike modal journey in the post-strike period. This suggests that those living in more distorted areas learned more from the strike.
tube  strike  rationality  optimisation  perturbation 
march 2018 by libbymiller
What are the Laws of Biology?
The core finding of systems biology is that only a very small subset of possible network motifs is actually used and that these motifs recur in all kinds of different systems, from transcriptional to biochemical to neural networks. This is because only those arrangements of interactions effectively perform some useful operation, which underlies some necessary function at a cellular or organismal level. There are different arrangements for input summation, input comparison, integration over time, high-pass or low-pass filtering, negative auto-regulation, coincidence detection, periodic oscillation, bistability, rapid onset response, rapid offset response, turning a graded signal into a sharp pulse or boundary, and so on, and so on.

These are all familiar concepts and designs in engineering and computing, with well-known properties. In living organisms there is one other general property that the designs must satisfy: robustness. They have to work with noisy components, at a scale that’s highly susceptible to thermal noise and environmental perturbations. Of the subset of designs that perform some operation, only a much smaller subset will do it robustly enough to be useful in a living organism. That is, they can still perform their particular functions in the face of noisy or fluctuating inputs or variation in the number of components constituting the elements of the network itself.
scitariat  reflection  proposal  ideas  thinking  conceptual-vocab  lens  bio  complex-systems  selection  evolution  flux-stasis  network-structure  structure  composition-decomposition  IEEE  robust  signal-noise  perturbation  interdisciplinary  graphs  circuits  🌞  big-picture  hi-order-bits  nibble  synthesis 
november 2017 by nhaliday
What Does a “Normal” Human Genome Look Like? | Science
So, what have our first glimpses of variation in the genomes of generally healthy people taught us? First, balancing selection, the evolutionary process that favors genetic diversification rather than the fixation of a single “best” variant, appears to play a minor role outside the immune system. Local adaptation, which accounts for variation in traits such as pigmentation, dietary specialization, and susceptibility to particular pathogens is also a second-tier player. What is on the top tier? Increasingly, the answer appears to be mutations that are “deleterious” by biochemical or standard evolutionary criteria. These mutations, as has long been appreciated, overwhelmingly make up the most abundant form of nonneutral variation in all genomes. A model for human genetic individuality is emerging in which there actually is a “wild-type” human genome—one in which most genes exist in an evolutionarily optimized form. There just are no “wild-type” humans: We each fall short of this Platonic ideal in our own distinctive ways.
article  essay  org:nat  🌞  bio  biodet  genetics  genomics  mutation  genetic-load  QTL  evolution  sapiens  survey  summary  coding-theory  enhancement  signal-noise  egalitarianism-hierarchy  selection  tradeoffs  immune  recent-selection  perturbation  nibble  ideas  forms-instances 
november 2017 by nhaliday
Stability of the Solar System - Wikipedia
The stability of the Solar System is a subject of much inquiry in astronomy. Though the planets have been stable when historically observed, and will be in the short term, their weak gravitational effects on one another can add up in unpredictable ways. For this reason (among others) the Solar System is chaotic,[1] and even the most precise long-term models for the orbital motion of the Solar System are not valid over more than a few tens of millions of years.[2]

The Solar System is stable in human terms, and far beyond, given that it is unlikely any of the planets will collide with each other or be ejected from the system in the next few billion years,[3] and the Earth's orbit will be relatively stable.[4]

Since Newton's law of gravitation (1687), mathematicians and astronomers (such as Laplace, Lagrange, Gauss, Poincaré, Kolmogorov, Vladimir Arnold and Jürgen Moser) have searched for evidence for the stability of the planetary motions, and this quest led to many mathematical developments, and several successive 'proofs' of stability of the Solar System.[5]

...

The planets' orbits are chaotic over longer timescales, such that the whole Solar System possesses a Lyapunov time in the range of 2–230 million years.[3] In all cases this means that the position of a planet along its orbit ultimately becomes impossible to predict with any certainty (so, for example, the timing of winter and summer become uncertain), but in some cases the orbits themselves may change dramatically. Such chaos manifests most strongly as changes in eccentricity, with some planets' orbits becoming significantly more—or less—elliptical.[7]

Is the Solar System Stable?: https://www.ias.edu/ideas/2011/tremaine-solar-system

Is the Solar System Stable?: https://arxiv.org/abs/1209.5996
nibble  wiki  reference  article  physics  mechanics  space  gravity  flux-stasis  uncertainty  robust  perturbation  math  dynamical  math.DS  volo-avolo  multi  org:edu  org:inst  papers  preprint  time  data  org:mat 
november 2017 by nhaliday
Universal adversarial perturbations
in today’s paper Moosavi-Dezfooli et al., show us how to create a _single_ perturbation that causes the vast majority of input images to be misclassified.
adversarial-classification  spam  image-recognition  ml  machine-learning  dnns  neural-networks  images  classification  perturbation  papers 
september 2017 by jm
How to Escape Saddle Points Efficiently – Off the convex path
A core, emerging problem in nonconvex optimization involves the escape of saddle points. While recent research has shown that gradient descent (GD) generically escapes saddle points asymptotically (see Rong Ge’s and Ben Recht’s blog posts), the critical open problem is one of efficiency — is GD able to move past saddle points quickly, or can it be slowed down significantly? How does the rate of escape scale with the ambient dimensionality? In this post, we describe our recent work with Rong Ge, Praneeth Netrapalli and Sham Kakade, that provides the first provable positive answer to the efficiency question, showing that, rather surprisingly, GD augmented with suitable perturbations escapes saddle points efficiently; indeed, in terms of rate and dimension dependence it is almost as if the saddle points aren’t there!
acmtariat  org:bleg  nibble  liner-notes  machine-learning  acm  optimization  gradient-descent  local-global  off-convex  time-complexity  random  perturbation  michael-jordan  iterative-methods  research  learning-theory  math.DS  iteration-recursion 
july 2017 by nhaliday
Is Pharma Research Worse Than Chance? | Slate Star Codex
Here’s one hypothesis: at the highest level, the brain doesn’t have that many variables to affect, or all the variables are connected. If you smack the brain really really hard in some direction or other, you will probably treat some psychiatric disease. Drugs of abuse are ones that smack the brain really hard in some direction or other. They do something. So find the psychiatric illness that’s treated by smacking the brain in that direction, and you’re good.

Actual carefully-researched psychiatric drugs are exquisitely selected for having few side effects. The goal is something like an SSRI – mild stomach discomfort, some problems having sex, but overall you can be on them forever and barely notice their existence. In the grand scheme of things their side effects are tiny – in most placebo-controlled studies, people have a really hard time telling whether they’re in the experimental or the placebo group.

...

But given that we’re all very excited to learn about ketamine and MDMA, and given that if their original promise survives further testing we will consider them great discoveries, it suggests we chose the wrong part of the tradeoff curve. Or at least it suggests a different way of framing that tradeoff curve. A drug that makes you feel extreme side effects for a few hours – but also has very strong and lasting treatment effects – is better than a drug with few side effects and weaker treatment effects. That suggests a new direction pharmaceutical companies might take: look for the chemicals that have the strongest and wackiest effects on the human mind. Then see if any of them also treat some disease.

I think this is impossible with current incentives. There’s too little risk-tolerance at every stage in the system. But if everyone rallied around the idea, it might be that trying the top hundred craziest things Alexander Shulgin dreamed up on whatever your rat model is would be orders of magnitude more productive than whatever people are doing now.
ratty  yvain  ssc  reflection  psychiatry  medicine  pharma  drugs  error  efficiency  random  meta:medicine  flexibility  outcome-risk  incentives  stagnation  innovation  low-hanging  tradeoffs  realness  perturbation  degrees-of-freedom  volo-avolo  null-result 
june 2017 by nhaliday
Orbital Perturbation
In astronomy, perturbation is the complex motion of a massive body subject to forces other than the gravitational attraction of a single other massive body. The other forces can include a third (fourth, fifth, etc.) body, resistance, as from an atmosphere, and the off-center attraction of an oblate or otherwise misshapen body.
perturbation  definition  orbit 
may 2017 by thespacedoctor
Polymorphisms and Load | West Hunter
Anyhow, we now have some estimates of the relative influence of common variants on various traits (from recent Visscher-type papers) . The fraction of genetic variation that can be explained by common variants is about half for height and IQ, one-third for schizophrenia, one-quarter for BMI, and about one-fifth for personality, as measured by standard personality measures, which I don’t have much faith in. If I had to guess, and at this point I do, the more that trait variation is a deviation from the selective optimum, rather than being orthogonal to fitness, the more it is influenced by load.
west-hunter  scitariat  discussion  biodet  behavioral-gen  genetics  QTL  population-genetics  genetic-load  data  iq  embodied  psychiatry  personality  stylized-facts  prediction  variance-components  correlation  evolution  sapiens  mutation  distribution  🌞  disease  health  fitness  psychology  cog-psych  spearhead  perturbation 
may 2017 by nhaliday

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