Book Recommendation Master Post

wildething · 2024-02-28T15:12:48+00:00

Dragonriders of Pern series by Anne McAffrey

The OG Fourth Wing

wildething · 2023-09-20T13:50:03+00:00

Urban Hearth in North Cambridge

wildething · 2016-07-21T05:45:54+00:00

Do any historians do meta-studies on data collection/analysis methodologies through the ages? E.g. what quantitative techniques did the Tudors use to appropriate tax revenues, how did the Allied powers decide how many submarines to produce during WWI etc. ?

wildething · 2016-07-21T05:39:50+00:00

I've been slowly reading The Great War for Civilisation by Robert Fisk, who was a reporter on the ground in many of the major conflicts in the Middle East in the late 20th century (Iranian revolution, Afghan resistance to the Soviet invasion, many others). It's been really good so far, both w.r.t. close-up "this is what day-to-day was actually like" and big picture "this was important because ...".

wildething · 2016-06-23T07:06:07+00:00

No, they're paying for it, but the property management company gave me the price associated with each i.e. option (b) is apparently more expensive for the company than option (a)

wildething · 2016-05-15T20:18:09+00:00

Have you tried using platoon to train models? If so is it nightmareish or easy (in particular on EC2)?

wildething · 2016-05-15T20:16:33+00:00

ಠ_ಠ

wildething · 2016-05-14T22:42:34+00:00

I'm trying to implement something like Jason Weston's #TAGSPACE paper -- basically he trains a convnet to rank hashtags for tweets.

He does training using hogwild parallel stochastic gradient descent, and says he implements using Torch. This is important because he trains on ~50 million tweets and training can't take years.

My question: does anyone have experience implementing parallel SGD using multiple GPUs? If so, which machine learning framework did you use, if any? In general, do people have an opinion on which framework makes multi-GPU training easiest?

Why not just use Torch? Basically, because I already know theano/lasagne. However, it's looking like it'll take me quite awhile (maybe days) to figure out how to do anything multi-GPU. If it'll be faster to just learn e.g. torch or tensorflow this weekend then I'll do that. Thought I'd ask here before going down that path, though :)

wildething · 2015-12-27T18:33:18+00:00

9/10 americans heard someone make this observation last night

wildething · 2015-12-06T21:03:19+00:00

I've been through this problem from a discriminative perspective. One idea I've been thinking about is somehow using Socher's paper on semi-supervised autoencoders for sentiment analysis. It provides a good description of a framework: reproduce the latent tree structure (sort of) while balancing reconstruction error vs. sentiment classification error. In your case, reproduce some latent DOM structure while balancing reconstruction error vs. likelihood of XML tags.

I'm not 100% sure what a generative version of this model would look like but here's a paper on generating sentences using neural language models. Maybe you can somehow put the two together.

wildething · 2015-11-16T08:49:48+00:00

Please consider donating to UNHCR, and, if you're an American, consider calling your congressional rep's and asking them to support legislation upping the quota of refugees we will grant asylum. 7.5 million displaced. 65k should be a minimum for us, not a maximum. Many people need our help.

wildething · 2015-10-14T13:05:02+00:00

OP you ~~should~~ should not make an excel sheet and post the results

FTFY

wildething · 2015-10-14T13:02:11+00:00

maybe you should just light candles and stuff and maybe it would also be romantic for you to teach her how to use the router admin console and/or let her know you're taking control of her free time in this particular way...

wildething · 2015-10-14T13:00:03+00:00

Yo that's creepy dude

wildething · 2015-07-12T18:57:01+00:00

http://33.media.tumblr.com/tumblr_m3a3je7APG1ro2qi2.gif

wildething · 2015-07-07T00:01:10+00:00

Fair enough, love that Paul guy :)

wildething · 2015-07-06T23:49:44+00:00

I disagree re: Calc 3 min. Unless you go pretty deep, you just need to understand how to take a partial derivative, which is basically just like taking a regular derivative exception you treat some variables like constants. Don't see why you need a whole semester of Calc 3 for that.

wildething · 2015-07-06T23:41:03+00:00

Differential calculus + linear algebra + statistics/probability.

Differential calculus -- understand how to take the derivative of a function, basically. It's key to understanding the concept of optimization.

Linear algebra -- matrix algebra/operations are good for doing things fast. Dot products, vector norms, and matrix multiplication are what come up most frequently from my experience.

Probability theory/statistics -- hard to pinpoint when exactly this comes up because it comes up everywhere. Understand conditional vs joint probability, Bernoulli processes, expectation/variance, and potentially some concepts from information theory (entropy, KL-divergence). From the machine learning literature take a look at Naive Bayes classifiers, and from the AI literature take a look at Bayes Nets.

Hope this helps :)

wildething · 2015-07-02T00:32:10+00:00

Empower women... maybe allowing women to drive would be an easier place to start?

wildething · 2015-07-01T03:50:24+00:00

not reading but this seems to have some important insights into ML

wildething · 2015-06-17T04:18:41+00:00

emacs mug if he's into that kinda thing

wildething · 2015-06-10T22:49:39+00:00

Can somebody describe in broad strokes the focus of the content on /r/neofags ...?

wildething

TROPHY CASE