This week we have
Anirudh Goyal from
Mila giving a talk on
Inductive Biases, Invariances and Generalization at
10h30 in room
Mila Auditorium.
Will this talk be
streamed ? yes
See you there!
The Tea Talk Team
TITLE Inductive Biases, Invariances and Generalization
ABSTRACT
The biggest challenge right now in RL specifically, AI more generally, is to devise methods for learning complex behaviours that have meaningful generalization. In supervised learning (vision, speech, NLP), it seems that deep models can achieve very complex generalization, but this is not really the case in RL. In this talk, I'm going to first argue that this gap in generalization has much to do with current practices in evaluating generalization in multitask, transfer and meta-learning setups, and then I'm going to talk about an elegant solution for learning complex inductive biases that can be used to exploit the structure of the task, thus enabling the learning agent to incorporate prior knowledge into the learning system to exploit reusable structure in task space.
BIO
Anirudh Goyal is a first year PhD student advised by Prof. Yoshua Bengio. His current research interests center around understanding the interplay b/w three words: Invariances, Inductive Biases and Generalization.