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diff --git a/pages/all-microposts.org b/pages/all-microposts.org deleted file mode 100644 index 92896bc..0000000 --- a/pages/all-microposts.org +++ /dev/null @@ -1,773 +0,0 @@ -#+title: Yuchen's Microblog - -*** 2020-08-02: ia-lawsuit - :PROPERTIES: - :CUSTOM_ID: ia-lawsuit - :END: -The four big publishers Hachette, HarperCollins, Wiley, and Penguin -Random House are still pursuing Internet Archive. - -#+begin_quote - [Their] lawsuit does not stop at seeking to end the practice of - Controlled Digital Lending. These publishers call for the destruction - of the 1.5 million digital books that Internet Archive makes available - to our patrons. This form of digital book burning is unprecedented and - unfairly disadvantages people with print disabilities. For the blind, - ebooks are a lifeline, yet less than one in ten exists in accessible - formats. Since 2010, Internet Archive has made our lending library - available to the blind and print disabled community, in addition to - sighted users. If the publishers are successful with their lawsuit, - more than a million of those books would be deleted from the - Internet's digital shelves forever. -#+end_quote - -[[https://blog.archive.org/2020/07/29/internet-archive-responds-to-publishers-lawsuit/][Libraries -lend books, and must continue to lend books: Internet Archive responds -to publishers' lawsuit]] -*** 2020-08-02: fsf-membership - :PROPERTIES: - :CUSTOM_ID: fsf-membership - :END: -I am a proud associate member of Free Software Freedom. For me the -philosophy of Free Software is about ensuring the enrichment of a -digital commons, so that knowledge and information are not concentrated -in the hands of selected privileged people and locked up as -"intellectual property". The genius of copyleft licenses like GNU (A)GPL -ensures software released for the public, remains public. Open source -does not care about that. - -If you also care about the public good, the hacker ethics, or the spirit -of the web, please take a moment to consider joining FSF as an associate -member. It comes with [[https://www.fsf.org/associate/benefits][numerous -perks and benefits]]. -*** 2020-06-21: how-can-you-help-ia - :PROPERTIES: - :CUSTOM_ID: how-can-you-help-ia - :END: -[[https://blog.archive.org/2020/06/14/how-can-you-help-the-internet-archive/][How -can you help the Internet Archive?]] Use it. It's more than the Wayback -Machine. And get involved. -*** 2020-06-12: open-library - :PROPERTIES: - :CUSTOM_ID: open-library - :END: -Open Library was cofounded by Aaron Swartz. As part of the Internet -Archive, it has done good work to spread knowledge. However it is -currently -[[https://arstechnica.com/tech-policy/2020/06/internet-archive-ends-emergency-library-early-to-appease-publishers/][being -sued by four major publishers]] for the -[[https://archive.org/details/nationalemergencylibrary][National -Emergency Library]]. IA decided to -[[https://blog.archive.org/2020/06/10/temporary-national-emergency-library-to-close-2-weeks-early-returning-to-traditional-controlled-digital-lending/][close -the NEL two weeks earlier than planned]], but the lawsuit is not over, -which in the worst case scenario has the danger of resulting in -Controlled Digital Lending being considered illegal and (less likely) -bancruptcy of the Internet Archive. If this happens it will be a big -setback of the free-culture movement. -*** 2020-04-15: sanders-suspend-campaign - :PROPERTIES: - :CUSTOM_ID: sanders-suspend-campaign - :END: -Suspending the campaign is different from dropping out of the race. -Bernie Sanders remains on the ballot, and indeed in his campaign -suspension speech he encouraged people to continue voting for him in the -democratic primaries to push for changes in the convention. -*** 2019-09-30: defense-stallman - :PROPERTIES: - :CUSTOM_ID: defense-stallman - :END: -Someone wrote a bold article titled -[[https://geoff.greer.fm/2019/09/30/in-defense-of-richard-stallman/]["In -Defense of Richard Stallman"]]. Kudos to him. - -Also, an interesting read: -[[https://cfenollosa.com/blog/famous-computer-public-figure-suffers-the-consequences-for-asshole-ish-behavior.html][Famous -public figure in tech suffers the consequences for asshole-ish -behavior]]. -*** 2019-09-29: stallman-resign - :PROPERTIES: - :CUSTOM_ID: stallman-resign - :END: -Last week Richard Stallman resigned from FSF. It is a great loss for the -free software movement. - -The apparent cause of his resignation and the events that triggered it -reflect some alarming trends of the zeitgeist. Here is a detailed review -of what happened: [[https://sterling-archermedes.github.io/][Low grade -"journalists" and internet mob attack RMS with lies. In-depth review.]]. -Some interesting articles on this are: -[[https://jackbaruth.com/?p=16779][Weekly Roundup: The Passion Of Saint -iGNUcius Edition]], -[[http://techrights.org/2019/09/17/rms-witch-hunt/][Why I Once Called -for Richard Stallman to Step Down]]. - -Dishonest and misleading media pieces involved in this incident include -[[https://www.thedailybeast.com/famed-mit-computer-scientist-richard-stallman-defends-epstein-victims-were-entirely-willing][The -Daily Beast]], -[[https://www.vice.com/en_us/article/9ke3ke/famed-computer-scientist-richard-stallman-described-epstein-victims-as-entirely-willing][Vice]], -[[https://techcrunch.com/2019/09/16/computer-scientist-richard-stallman-who-defended-jeffrey-epstein-resigns-from-mit-csail-and-the-free-software-foundation/][Tech -Crunch]], -[[https://www.wired.com/story/richard-stallmans-exit-heralds-a-new-era-in-tech/][Wired]]. -*** 2019-03-16: decss-haiku - :PROPERTIES: - :CUSTOM_ID: decss-haiku - :END: - -#+begin_quote - #+begin_example - Muse! When we learned to - count, little did we know all - the things we could do - - some day by shuffling - those numbers: Pythagoras - said "All is number" - - long before he saw - computers and their effects, - or what they could do - - by computation, - naive and mechanical - fast arithmetic. - - It changed the world, it - changed our consciousness and lives - to have such fast math - - available to - us and anyone who cared - to learn programming. - - Now help me, Muse, for - I wish to tell a piece of - controversial math, - - for which the lawyers - of DVD CCA - don't forbear to sue: - - that they alone should - know or have the right to teach - these skills and these rules. - - (Do they understand - the content, or is it just - the effects they see?) - - And all mathematics - is full of stories (just read - Eric Temple Bell); - - and CSS is - no exception to this rule. - Sing, Muse, decryption - - once secret, as all - knowledge, once unknown: how to - decrypt DVDs. - #+end_example -#+end_quote - -Seth Schoen, [[https://en.wikipedia.org/wiki/DeCSS_haiku][DeCSS haiku]] -*** 2019-01-27: learning-undecidable - :PROPERTIES: - :CUSTOM_ID: learning-undecidable - :END: -My take on the -[[https://www.nature.com/articles/s42256-018-0002-3][Nature paper -/Learning can be undecidable/]]: - -Fantastic article, very clearly written. - -So it reduces a kind of learninability called estimating the maximum -(EMX) to the cardinality of real numbers which is undecidable. - -When it comes to the relation between EMX and the rest of machine -learning framework, the article mentions that EMX belongs to "extensions -of PAC learnability include Vapnik's statistical learning setting and -the equivalent general learning setting by Shalev-Shwartz and -colleagues" (I have no idea what these two things are), but it does not -say whether EMX is representative of or reduces to common learning -tasks. So it is not clear whether its undecidability applies to ML at -large. - -Another condition to the main theorem is the union bounded closure -assumption. It seems a reasonable property of a family of sets, but then -again I wonder how that translates to learning. - -The article says "By now, we know of quite a few independence [from -mathematical axioms] results, mostly for set theoretic questions like -the continuum hypothesis, but also for results in algebra, analysis, -infinite combinatorics and more. Machine learning, so far, has escaped -this fate." but the description of the EMX learnability makes it more -like a classical mathematical / theoretical computer science problem -rather than machine learning. - -An insightful conclusion: "How come learnability can neither be proved -nor refuted? A closer look reveals that the source of the problem is in -defining learnability as the existence of a learning function rather -than the existence of a learning algorithm. In contrast with the -existence of algorithms, the existence of functions over infinite -domains is a (logically) subtle issue." - -In relation to practical problems, it uses an example of ad targeting. -However, A lot is lost in translation from the main theorem to this ad -example. - -The EMX problem states: given a domain X, a distribution P over X which -is unknown, some samples from P, and a family of subsets of X called F, -find A in F that approximately maximises P(A). - -The undecidability rests on X being the continuous [0, 1] interval, and -from the insight, we know the problem comes from the cardinality of -subsets of the [0, 1] interval, which is "logically subtle". - -In the ad problem, the domain X is all potential visitors, which is -finite because there are finite number of people in the world. In this -case P is a categorical distribution over the 1..n where n is the -population of the world. One can have a good estimate of the parameters -of a categorical distribution by asking for sufficiently large number of -samples and computing the empirical distribution. Let's call the -estimated distribution Q. One can choose the from F (also finite) the -set that maximises Q(A) which will be a solution to EMX. - -In other words, the theorem states: EMX is undecidable because not all -EMX instances are decidable, because there are some nasty ones due to -infinities. That does not mean no EMX instance is decidable. And I think -the ad instance is decidable. Is there a learning task that actually -corresponds to an undecidable EMX instance? I don't know, but I will not -believe the result of this paper is useful until I see one. - -h/t Reynaldo Boulogne -*** 2018-12-11: gavin-belson - :PROPERTIES: - :CUSTOM_ID: gavin-belson - :END: - -#+begin_quote - I don't know about you people, but I don't want to live in a world - where someone else makes the world a better place better than we do. -#+end_quote - -Gavin Belson, Silicon Valley S2E1. - -I came across this quote in -[[https://slate.com/business/2018/12/facebook-emails-lawsuit-embarrassing-mark-zuckerberg.html][a -Slate post about Facebook]] -*** 2018-10-05: margins - :PROPERTIES: - :CUSTOM_ID: margins - :END: -With Fermat's Library's new tool -[[https://fermatslibrary.com/margins][margins]], you can host your own -journal club. -*** 2018-09-18: rnn-turing - :PROPERTIES: - :CUSTOM_ID: rnn-turing - :END: -Just some non-rigorous guess / thought: Feedforward networks are like -combinatorial logic, and recurrent networks are like sequential logic -(e.g. data flip-flop is like the feedback connection in RNN). Since NAND -+ combinatorial logic + sequential logic = von Neumann machine which is -an approximation of the Turing machine, it is not surprising that RNN -(with feedforward networks) is Turing complete (assuming that neural -networks can learn the NAND gate). -*** 2018-09-07: zitierkartell - :PROPERTIES: - :CUSTOM_ID: zitierkartell - :END: -[[https://academia.stackexchange.com/questions/116489/counter-strategy-against-group-that-repeatedly-does-strategic-self-citations-and][Counter -strategy against group that repeatedly does strategic self-citations and -ignores other relevant research]] -*** 2018-09-05: short-science - :PROPERTIES: - :CUSTOM_ID: short-science - :END: - -#+begin_quote - - - ShortScience.org is a platform for post-publication discussion - aiming to improve accessibility and reproducibility of research - ideas. - - The website has over 800 summaries, mostly in machine learning, - written by the community and organized by paper, conference, and - year. - - Reading summaries of papers is useful to obtain the perspective and - insight of another reader, why they liked or disliked it, and their - attempt to demystify complicated sections. - - Also, writing summaries is a good exercise to understand the content - of a paper because you are forced to challenge your assumptions when - explaining it. - - Finally, you can keep up to date with the flood of research by - reading the latest summaries on our Twitter and Facebook pages. -#+end_quote - -[[https://shortscience.org][ShortScience.org]] -*** 2018-08-13: darknet-diaries - :PROPERTIES: - :CUSTOM_ID: darknet-diaries - :END: -[[https://darknetdiaries.com][Darknet Diaries]] is a cool podcast. -According to its about page it covers "true stories from the dark side -of the Internet. Stories about hackers, defenders, threats, malware, -botnets, breaches, and privacy." -*** 2018-06-20: coursera-basic-income - :PROPERTIES: - :CUSTOM_ID: coursera-basic-income - :END: -Coursera is having -[[https://www.coursera.org/learn/exploring-basic-income-in-a-changing-economy][a -Teach-Out on Basic Income]]. -*** 2018-06-19: pun-generator - :PROPERTIES: - :CUSTOM_ID: pun-generator - :END: -[[https://en.wikipedia.org/wiki/Computational_humor#Pun_generation][Pun -generators exist]]. -*** 2018-06-15: hackers-excerpt - :PROPERTIES: - :CUSTOM_ID: hackers-excerpt - :END: - -#+begin_quote - But as more nontechnical people bought computers, the things that - impressed hackers were not as essential. While the programs themselves - had to maintain a certain standard of quality, it was quite possible - that the most exacting standards---those applied by a hacker who - wanted to add one more feature, or wouldn't let go of a project until - it was demonstrably faster than anything else around---were probably - counterproductive. What seemed more important was marketing. There - were plenty of brilliant programs which no one knew about. Sometimes - hackers would write programs and put them in the public domain, give - them away as easily as John Harris had lent his early copy of - Jawbreaker to the guys at the Fresno computer store. But rarely would - people ask for public domain programs by name: they wanted the ones - they saw advertised and discussed in magazines, demonstrated in - computer stores. It was not so important to have amazingly clever - algorithms. Users would put up with more commonplace ones. - - The Hacker Ethic, of course, held that every program should be as good - as you could make it (or better), infinitely flexible, admired for its - brilliance of concept and execution, and designed to extend the user's - powers. Selling computer programs like toothpaste was heresy. But it - was happening. Consider the prescription for success offered by one of - a panel of high-tech venture capitalists, gathered at a 1982 software - show: "I can summarize what it takes in three words: marketing, - marketing, marketing." When computers are sold like toasters, programs - will be sold like toothpaste. The Hacker Ethic notwithstanding. -#+end_quote - -[[http://www.stevenlevy.com/index.php/books/hackers][Hackers: Heroes of -Computer Revolution]], by Steven Levy. -*** 2018-06-11: catalan-overflow - :PROPERTIES: - :CUSTOM_ID: catalan-overflow - :END: -To compute Catalan numbers without unnecessary overflow, use the -recurrence formula \(C_n = {4 n - 2 \over n + 1} C_{n - 1}\). -*** 2018-06-04: boyer-moore - :PROPERTIES: - :CUSTOM_ID: boyer-moore - :END: -The -[[https://en.wikipedia.org/wiki/Boyer–Moore_majority_vote_algorithm][Boyer-Moore -algorithm for finding the majority of a sequence of elements]] falls in -the category of "very clever algorithms". - -#+begin_example - int majorityElement(vector<int>& xs) { - int count = 0; - int maj = xs[0]; - for (auto x : xs) { - if (x == maj) count++; - else if (count == 0) maj = x; - else count--; - } - return maj; - } -#+end_example -*** 2018-05-30: how-to-learn-on-your-own - :PROPERTIES: - :CUSTOM_ID: how-to-learn-on-your-own - :END: -Roger Grosse's post -[[https://metacademy.org/roadmaps/rgrosse/learn_on_your_own][How to -learn on your own (2015)]] is an excellent modern guide on how to learn -and research technical stuff (especially machine learning and maths) on -one's own. -*** 2018-05-25: 2048-mdp - :PROPERTIES: - :CUSTOM_ID: 2048-mdp - :END: -[[http://jdlm.info/articles/2018/03/18/markov-decision-process-2048.html][This -post]] models 2048 as an MDP and solves it using policy iteration and -backward induction. -*** 2018-05-22: ats - :PROPERTIES: - :CUSTOM_ID: ats - :END: - -#+begin_quote - ATS (Applied Type System) is a programming language designed to unify - programming with formal specification. ATS has support for combining - theorem proving with practical programming through the use of advanced - type systems. A past version of The Computer Language Benchmarks Game - has demonstrated that the performance of ATS is comparable to that of - the C and C++ programming languages. By using theorem proving and - strict type checking, the compiler can detect and prove that its - implemented functions are not susceptible to bugs such as division by - zero, memory leaks, buffer overflow, and other forms of memory - corruption by verifying pointer arithmetic and reference counting - before the program compiles. Additionally, by using the integrated - theorem-proving system of ATS (ATS/LF), the programmer may make use of - static constructs that are intertwined with the operative code to - prove that a function attains its specification. -#+end_quote - -[[https://en.wikipedia.org/wiki/ATS_(programming_language)][Wikipedia -entry on ATS]] -*** 2018-05-20: bostoncalling - :PROPERTIES: - :CUSTOM_ID: bostoncalling - :END: -(5-second fame) I sent a picture of my kitchen sink to BBC and got -mentioned in the [[https://www.bbc.co.uk/programmes/w3cswg8c][latest -Boston Calling episode]] (listen at 25:54). -*** 2018-05-18: colah-blog - :PROPERTIES: - :CUSTOM_ID: colah-blog - :END: -[[https://colah.github.io/][colah's blog]] has a cool feature that -allows you to comment on any paragraph of a blog post. Here's an -[[https://colah.github.io/posts/2015-08-Understanding-LSTMs/][example]]. -If it is doable on a static site hosted on Github pages, I suppose it -shouldn't be too hard to implement. This also seems to work more -seamlessly than [[https://fermatslibrary.com/][Fermat's Library]], -because the latter has to embed pdfs in webpages. Now fantasy time: -imagine that one day arXiv shows html versions of papers (through author -uploading or conversion from TeX) with this feature. -*** 2018-05-15: random-forests - :PROPERTIES: - :CUSTOM_ID: random-forests - :END: -[[https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/info][Stanford -Lagunita's statistical learning course]] has some excellent lectures on -random forests. It starts with explanations of decision trees, followed -by bagged trees and random forests, and ends with boosting. From these -lectures it seems that: - -1. The term "predictors" in statistical learning = "features" in machine - learning. -2. The main idea of random forests of dropping predictors for individual - trees and aggregate by majority or average is the same as the idea of - dropout in neural networks, where a proportion of neurons in the - hidden layers are dropped temporarily during different minibatches of - training, effectively averaging over an emsemble of subnetworks. Both - tricks are used as regularisations, i.e. to reduce the variance. The - only difference is: in random forests, all but a square root number - of the total number of features are dropped, whereas the dropout - ratio in neural networks is usually a half. - -By the way, here's a comparison between statistical learning and machine -learning from the slides of the Statistcal Learning course: -*** 2018-05-14: open-review-net - :PROPERTIES: - :CUSTOM_ID: open-review-net - :END: -Open peer review means peer review process where communications -e.g. comments and responses are public. - -Like [[https://scipost.org/][SciPost]] mentioned in -[[/posts/2018-04-10-update-open-research.html][my post]], -[[https://openreview.net][OpenReview.net]] is an example of open peer -review in research. It looks like their focus is machine learning. Their -[[https://openreview.net/about][about page]] states their mission, and -here's [[https://openreview.net/group?id=ICLR.cc/2018/Conference][an -example]] where you can click on each entry to see what it is like. We -definitely need this in the maths research community. -*** 2018-05-11: rnn-fsm - :PROPERTIES: - :CUSTOM_ID: rnn-fsm - :END: -Related to [[#neural-turing-machine][a previous micropost]]. - -[[http://www.cs.toronto.edu/~rgrosse/csc321/lec9.pdf][These slides from -Toronto]] are a nice introduction to RNN (recurrent neural network) from -a computational point of view. It states that RNN can simulate any FSM -(finite state machine, a.k.a. finite automata abbr. FA) with a toy -example computing the parity of a binary string. - -[[http://www.deeplearningbook.org/contents/rnn.html][Goodfellow et. -al.'s book]] (see page 372 and 374) goes one step further, stating that -RNN with a hidden-to-hidden layer can simulate Turing machines, and not -only that, but also the /universal/ Turing machine abbr. UTM (the book -referenced -[[https://www.sciencedirect.com/science/article/pii/S0022000085710136][Siegelmann-Sontag]]), -a property not shared by the weaker network where the hidden-to-hidden -layer is replaced by an output-to-hidden layer (page 376). - -By the way, the RNN with a hidden-to-hidden layer has the same -architecture as the so-called linear dynamical system mentioned in -[[https://www.coursera.org/learn/neural-networks/lecture/Fpa7y/modeling-sequences-a-brief-overview][Hinton's -video]]. - -From what I have learned, the universality of RNN and feedforward -networks are therefore due to different arguments, the former coming -from Turing machines and the latter from an analytical view of -approximation by step functions. -*** 2018-05-10: math-writing-decoupling - :PROPERTIES: - :CUSTOM_ID: math-writing-decoupling - :END: -One way to write readable mathematics is to decouple concepts. One idea -is the following template. First write a toy example with all the -important components present in this example, then analyse each -component individually and elaborate how (perhaps more complex) -variations of the component can extend the toy example and induce more -complex or powerful versions of the toy example. Through such -incremental development, one should be able to arrive at any result in -cutting edge research after a pleasant journey. - -It's a bit like the UNIX philosophy, where you have a basic system of -modules like IO, memory management, graphics etc, and modify / improve -each module individually (H/t [[http://nand2tetris.org/][NAND2Tetris]]). - -The book [[http://neuralnetworksanddeeplearning.com/][Neutral networks -and deep learning]] by Michael Nielsen is an example of such approach. -It begins the journey with a very simple neutral net with one hidden -layer, no regularisation, and sigmoid activations. It then analyses each -component including cost functions, the back propagation algorithm, the -activation functions, regularisation and the overall architecture (from -fully connected to CNN) individually and improve the toy example -incrementally. Over the course the accuracy of the example of mnist -grows incrementally from 95.42% to 99.67%. -*** 2018-05-09: neural-turing-machine - :PROPERTIES: - :CUSTOM_ID: neural-turing-machine - :END: - -#+begin_quote - One way RNNs are currently being used is to connect neural networks - more closely to traditional ways of thinking about algorithms, ways of - thinking based on concepts such as Turing machines and (conventional) - programming languages. [[https://arxiv.org/abs/1410.4615][A 2014 - paper]] developed an RNN which could take as input a - character-by-character description of a (very, very simple!) Python - program, and use that description to predict the output. Informally, - the network is learning to "understand" certain Python programs. - [[https://arxiv.org/abs/1410.5401][A second paper, also from 2014]], - used RNNs as a starting point to develop what they called a neural - Turing machine (NTM). This is a universal computer whose entire - structure can be trained using gradient descent. They trained their - NTM to infer algorithms for several simple problems, such as sorting - and copying. - - As it stands, these are extremely simple toy models. Learning to - execute the Python program =print(398345+42598)= doesn't make a - network into a full-fledged Python interpreter! It's not clear how - much further it will be possible to push the ideas. Still, the results - are intriguing. Historically, neural networks have done well at - pattern recognition problems where conventional algorithmic approaches - have trouble. Vice versa, conventional algorithmic approaches are good - at solving problems that neural nets aren't so good at. No-one today - implements a web server or a database program using a neural network! - It'd be great to develop unified models that integrate the strengths - of both neural networks and more traditional approaches to algorithms. - RNNs and ideas inspired by RNNs may help us do that. -#+end_quote - -Michael Nielsen, -[[http://neuralnetworksanddeeplearning.com/chap6.html#other_approaches_to_deep_neural_nets][Neural -networks and deep learning]] -*** 2018-05-09: neural-nets-activation - :PROPERTIES: - :CUSTOM_ID: neural-nets-activation - :END: - -#+begin_quote - What makes the rectified linear activation function better than the - sigmoid or tanh functions? At present, we have a poor understanding of - the answer to this question. Indeed, rectified linear units have only - begun to be widely used in the past few years. The reason for that - recent adoption is empirical: a few people tried rectified linear - units, often on the basis of hunches or heuristic arguments. They got - good results classifying benchmark data sets, and the practice has - spread. In an ideal world we'd have a theory telling us which - activation function to pick for which application. But at present - we're a long way from such a world. I should not be at all surprised - if further major improvements can be obtained by an even better choice - of activation function. And I also expect that in coming decades a - powerful theory of activation functions will be developed. Today, we - still have to rely on poorly understood rules of thumb and experience. -#+end_quote - -Michael Nielsen, -[[http://neuralnetworksanddeeplearning.com/chap6.html#convolutional_neural_networks_in_practice][Neutral -networks and deep learning]] -*** 2018-05-08: sql-injection-video - :PROPERTIES: - :CUSTOM_ID: sql-injection-video - :END: -Computerphile has some brilliant educational videos on computer science, -like [[https://www.youtube.com/watch?v=ciNHn38EyRc][a demo of SQL -injection]], [[https://www.youtube.com/watch?v=eis11j_iGMs][a toy -example of the lambda calculus]], and -[[https://www.youtube.com/watch?v=9T8A89jgeTI][explaining the Y -combinator]]. -*** 2018-05-08: nlp-arxiv - :PROPERTIES: - :CUSTOM_ID: nlp-arxiv - :END: -Primer Science is a tool by a startup called Primer that uses NLP to -summarize contents (but not single papers, yet) on arxiv. A developer of -this tool predicts in -[[https://twimlai.com/twiml-talk-136-taming-arxiv-w-natural-language-processing-with-john-bohannon/#][an -interview]] that progress on AI's ability to extract meanings from AI -research papers will be the biggest accelerant on AI research. -*** 2018-05-08: neural-nets-regularization - :PROPERTIES: - :CUSTOM_ID: neural-nets-regularization - :END: - -#+begin_quote - no-one has yet developed an entirely convincing theoretical - explanation for why regularization helps networks generalize. Indeed, - researchers continue to write papers where they try different - approaches to regularization, compare them to see which works better, - and attempt to understand why different approaches work better or - worse. And so you can view regularization as something of a kludge. - While it often helps, we don't have an entirely satisfactory - systematic understanding of what's going on, merely incomplete - heuristics and rules of thumb. - - There's a deeper set of issues here, issues which go to the heart of - science. It's the question of how we generalize. Regularization may - give us a computational magic wand that helps our networks generalize - better, but it doesn't give us a principled understanding of how - generalization works, nor of what the best approach is. -#+end_quote - -Michael Nielsen, -[[http://neuralnetworksanddeeplearning.com/chap3.html#why_does_regularization_help_reduce_overfitting][Neural -networks and deep learning]] -*** 2018-05-07: learning-knowledge-graph-reddit-journal-club - :PROPERTIES: - :CUSTOM_ID: learning-knowledge-graph-reddit-journal-club - :END: -It is a natural idea to look for ways to learn things like going through -a skill tree in a computer RPG. - -For example I made a -[[https://ypei.me/posts/2015-04-02-juggling-skill-tree.html][DAG for -juggling]]. - -Websites like [[https://knowen.org][Knowen]] and -[[https://metacademy.org][Metacademy]] explore this idea with added -flavour of open collaboration. - -The design of Metacademy looks quite promising. It also has a nice -tagline: "your package manager for knowledge". - -There are so so many tools to assist learning / research / knowledge -sharing today, and we should keep experimenting, in the hope that -eventually one of them will scale. - -On another note, I often complain about the lack of a place to discuss -math research online, but today I found on Reddit some journal clubs on -machine learning: -[[https://www.reddit.com/r/MachineLearning/comments/8aluhs/d_machine_learning_wayr_what_are_you_reading_week/][1]], -[[https://www.reddit.com/r/MachineLearning/comments/8elmd8/d_anyone_having_trouble_reading_a_particular/][2]]. -If only we had this for maths. On the other hand r/math does have some -interesting recurring threads as well: -[[https://www.reddit.com/r/math/wiki/everythingaboutx][Everything about -X]] and -[[https://www.reddit.com/r/math/search?q=what+are+you+working+on?+author:automoderator+&sort=new&restrict_sr=on&t=all][What -Are You Working On?]]. Hopefully these threads can last for years to -come. -*** 2018-05-02: simple-solution-lack-of-math-rendering - :PROPERTIES: - :CUSTOM_ID: simple-solution-lack-of-math-rendering - :END: -The lack of maths rendering in major online communication platforms like -instant messaging, email or Github has been a minor obsession of mine -for quite a while, as I saw it as a big factor preventing people from -talking more maths online. But today I realised this is totally a -non-issue. Just do what people on IRC have been doing since the -inception of the universe: use a (latex) pastebin. -*** 2018-05-01: neural-networks-programming-paradigm - :PROPERTIES: - :CUSTOM_ID: neural-networks-programming-paradigm - :END: - -#+begin_quote - Neural networks are one of the most beautiful programming paradigms - ever invented. In the conventional approach to programming, we tell - the computer what to do, breaking big problems up into many small, - precisely defined tasks that the computer can easily perform. By - contrast, in a neural network we don't tell the computer how to solve - our problem. Instead, it learns from observational data, figuring out - its own solution to the problem at hand. -#+end_quote - -Michael Nielsen - -[[http://neuralnetworksanddeeplearning.com/about.html][What this book -(Neural Networks and Deep Learning) is about]] - -Unrelated to the quote, note that Nielsen's book is licensed under -[[https://creativecommons.org/licenses/by-nc/3.0/deed.en_GB][CC BY-NC]], -so one can build on it and redistribute non-commercially. -*** 2018-04-30: google-search-not-ai - :PROPERTIES: - :CUSTOM_ID: google-search-not-ai - :END: - -#+begin_quote - But, users have learned to accommodate to Google not the other way - around. We know what kinds of things we can type into Google and what - we can't and we keep our searches to things that Google is likely to - help with. We know we are looking for texts and not answers to start a - conversation with an entity that knows what we really need to talk - about. People learn from conversation and Google can't have one. It - can pretend to have one using Siri but really those conversations tend - to get tiresome when you are past asking about where to eat. -#+end_quote - -Roger Schank - -[[http://www.rogerschank.com/fraudulent-claims-made-by-IBM-about-Watson-and-AI][Fraudulent -claims made by IBM about Watson and AI]] -*** 2018-04-06: hacker-ethics - :PROPERTIES: - :CUSTOM_ID: hacker-ethics - :END: - -#+begin_quote - - - Access to computers---and anything that might teach you something - about the way the world works---should be unlimited and total. - Always yield to the Hands-On Imperative! - - All information should be free. - - Mistrust Authority---Promote Decentralization. - - Hackers should be judged by their hacking, not bogus criteria such - as degrees, age, race, or position. - - You can create art and beauty on a computer. - - Computers can change your life for the better. -#+end_quote - -[[https://en.wikipedia.org/wiki/Hacker_ethic][The Hacker Ethic]], -[[https://en.wikipedia.org/wiki/Hackers:_Heroes_of_the_Computer_Revolution][Hackers: -Heroes of Computer Revolution]], by Steven Levy -*** 2018-03-23: static-site-generator - :PROPERTIES: - :CUSTOM_ID: static-site-generator - :END: - -#+begin_quote - "Static site generators seem like music databases, in that everyone - eventually writes their own crappy one that just barely scratches the - itch they had (and I'm no exception)." -#+end_quote - -__david__@hackernews - -So did I. |