ArtificialIntelligenceArticles
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3. Deep Learning
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Dynamical, symplectic and stochastic perspectives on optimization

Michael Jordan – ICM2018 : https://youtu.be/wXNWVhE2Dl4 @ArtificialIntelligenceArticles
The mathematics of machine learning and deep learning – Sanjeev Arora – ICM2018 https://goo.gl/vj2yCF @ArtificialIntelligenceArticles
Why building your own Deep Learning computer is 10x cheaper than AWS

https://goo.gl/4ZbUf8 @ArtificialIntelligenceArticles
Speech and Language Processing (3rd ed. draft)
Dan Jurafsky and James H. Martin : https://web.stanford.edu/~jurafsky/slp3/
Series of Jupyter Notebooks with step-by-step introduction to data science and machine learning

Code : https://github.com/rasbt/python-machine-learning-book-2nd-edition
Computer Vision dataset search

visualdata.io is a great resource for exploring computer vision datasets : https://www.visualdata.io/
ICLR 2019 submission is closed and papers are now available to view

Nearly 1600 submissions received: https://openreview.net/group?id=ICLR.cc%2F2019%2FConference
Rules of Machine Learning: Best Practices for ML Engineering

By Martin Zinkevich: https://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf
Understanding & Generalizing AlphaGo Zero #ICLR2019

Anonymous: https://openreview.net/forum?id=rkxtl3C5YX
Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks [106pp]

Reviews recent literature in a comprehensive way, and provides an in-depth view of recent advances, current challenges, problem extensions and datasets.

https://arxiv.org/abs/1809.03193 @ArtificialIntelligenceArticles
How to train your MAML

By Anonymous: https://openreview.net/forum?id=HJGven05Y7

'TL;DR: MAML is great, but it has many problems, we solve many of those problems and as a result we learn most hyper parameters end to end, speed-up training and inference and set a new SOTA in few-shot learning'

#metalearning #deeplearning #fewshotlearning
On the Turing Completeness of Modern Neural Network Architectures

By Anonymous: https://openreview.net/forum?id=HyGBdo0qFm @ArtificialIntelligenceArticles
An Introduction to Probabilistic Programming

By Jan-Willem van de Meent, Brooks Paige, Hongseok Yang, Frank Wood: https://arxiv.org/abs/1809.10756 @ArtificialIntelligenceArticles
Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions https://openreview.net/forum?id=r1eEG20qKQ
A Review of the Recent History of Natural Language Processing

By Sebastian Ruder: https://blog.aylien.com/a-review-of-the-recent-history-of-natural-language-processing/