Chapter 1: Introduction to Machine Learning and Deep Learning
The first chapter (draft) of the Introduction to Deep Learning book, which is a book based on my lecture notes and slides.
deep-learning, Machine Learning
Machine Learning, Reinforcement
HOMER: Provable Exploration in Reinforcement Learning
Last week at ICML 2020, Mikael Henaff, Akshay Krishnamurthy, John Langford and I had a paper on a new reinforcement learning (RL) algorithm that solves three key problems in RL: (i) global exploration, (ii) decoding latent dynamics, and (iii) optimizing a given reward function. Our ICML poster is here. The paper is a bit mathematically heavy in nature so this …
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OpenAI Scholars 2020: Final projects
Our third class of OpenAI Scholars presented their final projects at virtual Demo Day, showcasing their research results from over the past five months.
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June gwern.net newsletter
June 2020 gwern.net newsletter with 3 new pages/essays, and links on CRISPR, population screening, AI scaling, politics, and technological unemployment.
ai, Career, deep-learning, Machine Learning, reinforcement-learning
Free Office Hours for Non-Traditional ML Researchers
Xiaoyi Yin (尹肖贻) has kindly translated this post into Chinese (中文)This post was prompted by a tweet I saw from my colleague, Colin:I’m currently a researcher at Google with a “non-traditional background”, where non-traditional background means “so…
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Procgen and MineRL Competitions
We’re excited to announce that OpenAI is co-organizing two NeurIPS 2020 competitions with AIcrowd, Carnegie Mellon University, and DeepMind, using Procgen Benchmark and MineRL.