Machine Learning (Theory)
Machine learning and learning theory research
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Latest posts
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Curbing AI with Flight Recorders, Brainwash Entrapment Tests, and 3rd Party Evaluation
I visited Adam Kalai’s new RESI AI Safety nonprofit last week and found it stimulating. Here is an approach which uses the properties of AI to curb AI harder than I have seen elsewhere. It’s not a complete solution of course, but silver bullet thinking seems inappropriate to…
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Agentic Coding Ascension Notes
I’ve found agentic coding (with Anthropic’s Claude) to be something between an x10 and x100 multiplier on what I personally can do in a software engineering vein. This seems to be significantly more than what other folks are observing, so I wanted to share some notes on how I…
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Headroom for AI development
(Dylan Foster and Alex Lamb both helped in creating this.) In thinking about what are good research problems, it’s sometimes helpful to switch from what is understood to what is clearly possible. This encourages us to think beyond simply improving the existing system. For…
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An AI Miracle Malcontent
The stark success of OpenAI’s GPT4 model surprised me shifting my view from “really good autocomplete” (roughly inline with intuitions here) to a dialog agent exhibiting a significant scope of reasoning and intelligence. Some of the MSR folks did a fairly thorough study of…
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ICML 2021 Invited Speakers — ML for Science
By: Stefanie Jegelka and Ameet Talwalkar (ICML21 Communication Chairs) With ICML 2021 underway, we wanted to briefly highlight the upcoming invited talks. A general theme of the invited talks this year is “machine learning for science.” The Program Chairs (Marina Meila and Tong…
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ALT Highlights – An Interview with Joelle Pineau
Welcome to ALT Highlights, a series of blog posts spotlighting various happenings at the recent conference ALT 2021, including plenary talks, tutorials, trends in learning theory, and more! To reach a broad audience, the series will be disseminated as guest posts on different…
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What is the Right Response to Employer Misbehavior in Research?
I enjoyed my conversations with Timnit when she was in the MSR-NYC lab, so her situation has been on my mind throughout NeurIPS. Piecing together what happened second-hand is always tricky, but Jeff Dean’s account and Timnit’s agree on a basic outline. Timnit and others wrote a…
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Experiments with the ICML 2020 Peer-Review Process
This post is cross-listed on the CMU ML blog. The International Conference on Machine Learning (ICML) is a flagship machine learning conference that in 2020 received 4,990 submissions and managed a pool of 3,931 reviewers and area chairs. Given that the stakes in the review…
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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.…
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Critical issues in digital contract tracing
I spent the last month becoming a connoisseur of digital contact tracing approaches since this seems like something where I might be able to help. Many other people have been thinking along similar lines (great), but I also see several misconceptions that even smart and deeply…