aviv-tamar.bsky.social
AI and robotics researcher at Technion
avivt.github.io/avivt/
16 posts
543 followers
62 following
Getting Started
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They performed well enough to make us believe that we can seriously spend $$$ to train a model to generate images that look real.
StyleGAN was the first time "deep fakes" became a real thing.
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I could never remember the git commands beyond commit/push/pull, but I find that chatGPT is very good at helping me with it whenever I need
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Thanks. At a high level, I see search heuristics to be quite similar to value functions. In the book, we prove A* optimality by "reward shaping" Dijkstra's algorithm, which is another connection between search heuristics and values.
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There's a fairly large RL Theory community.
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Completely agree.
Recently I got a review (for a journal) that was from a relevant expert who also signed his name at the end (he didn't need to). Made us take the review very very seriously, even though it was negative.
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ahm ahm... we just posted this today :)
bsky.app/profile/aviv...
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Yes, when I teach I also have a final "hand waving" class on deep RL where I show how to go from the textbook material to DQN, PPO, Alpha Go. Adding such comments is a good idea, thanks!
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We don't really cover deep RL algorithms. There's a lot on Q learning, and the distance from what we cover to DQN is very small. Actually, it would be a good idea to add a remark on that, thanks!
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🎯
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We hope you find it useful!
The book is still work in progress - we’d be grateful for comments, suggestions, omissions, and errors of any kind, at [email protected]
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But for teaching RL, we wanted a book that is both rigorous (full proofs and analytical examples), covers what we feel is most relevant, and is easy enough for undergrad teaching.
The book is a focused one semester course for advanced undergrad/early grad that covers key topics in depth.
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For teachers, we also have a 40+ page exam booklet on our website.
Why this book? 

There are several other excellent textbooks, including Sutton and Barto and Bertsekas and Tsitsiklis.
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The "bad reviewer party" sounds much more fun tho
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yes, this is a great paper!