The recording of the talk I gave at the @CIFAR_News DLRL Summer School this year at @VectorInst in Toronto is now publicly available:
I discussed the interaction between RL and games (with many historical notes).
RL and Games: youtube.com/watch?v=lwT05l…
Now that @RL_Conference is over (and what a success it was!), it's time to start thinking about the next one.
If you haven't heard yet, RLC is going north. We'll be organizing RLC'25 in Edmonton! I'm very excited about that and look forward to seeing everyone there.
Now that I have started using twitter somewhat regularly, let me take a minute to advertise the RL theory lecture notes I have been developing with Sasha Rakhlin: arxiv.org/abs/2312.16730
Final version is out, on the topic of mechanisms by which small cognitive subunits can scale up into larger collective intelligences:
"Stress sharing as cognitive glue for collective intelligences: A computational model of stress as a coordinator for morphogenesis"…
🚨@RL_Conference's Finding the Frame Workshop submission deadline is coming up on May 15! 🚨
Help us re-think the conceptual foundations of RL, that often go unchallenged. Tell us how YOU think problems should be framed. Create the next paradigm shift✨🚀
sites.google.com/view/findingth…
Now, as an Assistant Professor, I'll be growing my group more at the University of Alberta.
I'll continue to focus on ML and, specifically, reinforcement learning.
I'll be hiring PhD and thesis-based MSc students. I'm also hiring a postdoc now. See post: webdocs.cs.ualberta.ca/~machado/postd…
Echenle la leidita. Con @msantosvega llevamos echándole cabeza desde que nos conocemos a esto y @samueltorresfv nos ayudó a hacerlo realidad en medio de la pandemia.
Echenle la leidita. Con @msantosvega llevamos echándole cabeza desde que nos conocemos a esto y @samueltorresfv nos ayudó a hacerlo realidad en medio de la pandemia.
After a long beta, we are launching!
Connected Papers is a unique, visual tool to help researchers and applied scientists find and explore papers relevant to their field of work.
connectedpapers.com
BERT is very good at being right for the wrong reasons.
Great analysis of BERT's ability to learn exploiting annotation artifacts better than other models: arxiv.org/abs/1907.07355
Performance drops from 77% to random chance level when these artifacts are removed.
How would I know if my own research area was this wrong?
Our usual safeguards won’t save us: peer review, meta-analysis, 100s of conceptual replications, listening to eminent researchers. All failed.
This should be keeping us up at night.
slatestarcodex.com/2019/05/07/5-h…
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Mathematical Foundations of AI,
Complex Dynamical Systems, ML
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Bluesky: https://t.co/cU3TtyokJE
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Previously @rlai_lab UAlberta, @berkeley_ai, @MetaAI, @iitmadras. Opinions, if you find any, are my dog’s.
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Group page: https://t.co/yzv5n3vvRz
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Former: Postdoc @TU_Muenchen, @UniHeidelberg
Mathematical Foundations of AI,
Complex Dynamical Systems, ML
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