Shibhansh Dohare
shibhansh.bsky.social
Shibhansh Dohare
@shibhansh.bsky.social
AI researcher at University of Alberta.
https://shibhansh.github.io/
Reposted by Shibhansh Dohare
But injecting noise on the weights of quiescent neurons can:

www.nature.com/articles/s41...

So a bit of random homeostatic plasticity should do the trick.
Loss of plasticity in deep continual learning - Nature
The pervasive problem of artificial neural networks losing plasticity in continual-learning settings is demonstrated and a simple solution called the continual backpropagation algorithm is descri...
www.nature.com
November 27, 2024 at 3:00 PM
Reposted by Shibhansh Dohare
This year's (first-ever) RL conference was a breath of fresh air! And now that it's established, the next edition is likely to be even better: Consider sending your best and most original RL work there, and then join us in Edmonton next summer!
The call for papers for RLC is now up! Abstract deadline of 2/14, submission deadline of 2/21!
Please help us spread the word.
rl-conference.cc/callforpaper...
RLJ | RLC Call for Papers
rl-conference.cc
December 2, 2024 at 7:37 PM
Reposted by Shibhansh Dohare
Streaming Deep Reinforcement Learning Finally Works, by
M. Elsayed, G. Vasan, A. R. Mahmood, is one of those papers I wish I had written 😅

This paper seems to allow us to do RL with NNs as it should have always been done. Everyone should read it!

arxiv.org/abs/2410.14606
Streaming Deep Reinforcement Learning Finally Works
Natural intelligence processes experience as a continuous stream, sensing, acting, and learning moment-by-moment in real time. Streaming learning, the modus operandi of classic reinforcement learning ...
arxiv.org
November 27, 2024 at 11:09 PM