Grading Complex Interactive Coding Programs with Reinforcement Learning

[Summary] tl;dr: A tremendous amount of effort has been poured into training AI algorithms to competitively play games that computers have traditionally had trouble with, such as the retro games published by Atari, Go, DotA, and StarCraft II. The practical machine learning knowledge accumulated in developing these algorithms has paved...

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A Generative Model of Discourse

Short Preface

There has been a lot interests on sentence representation learning, similar to the explosion of word embedding.

Based on my limited education in linguistics, I do not believe linguistis have an agreed upon and exhaustive set of “properties” that a sentence representation1...

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A Tutorial on Torchtext

About 2-3 months ago, I encountered this library: Torchtext. I nonchalantly scanned through the README file and realize I have no idea how to use it or what kind of problem is it solving. I moved on.

Last week, there was a paper deadline, and I was tasked to...

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A Collection of Numpy Tricks

Numpy Array overrides many operations, so deciphering them could be uneasy. Here are a collection of what I would consider tricky/handy moments from Numpy.

Trick 1: Collection1 == Collection2

The == in Numpy, when applied to two collections mean element-wise comparison, and the returned result is an...

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Understand Numpy Reshape, Transpose, and Theano Dimshuffle

When you work with Numpy, you work with multidimensional arrays (or tensors). I have to admit such concept was not too easy for me to grasp in the beginning, but after some delibration, it became relatively easy. This post uses the term tensor/multidimensional array interchangeably.

for a tensor of shape...

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