Education
Contrastive Reinforcement Learning of Symbolic Reasoning Domains
Policy Learning (ConPoLe) that explicitly optimizes the InfoNCE loss, which lower bounds the mutual information between the current state and next states that continue on a path to the solution.
Fast geometric learning with symbolic matrices Jean Feydy
We perform an extensive evaluation on a broad class of problems: Gaussian modelling, K-nearest neighbors search, geometric deep learning, non-Euclidean embeddings and optimal transport theory.
Dual_Extrapolation_full (1)
This work was conducted during Chaobing Song's visit to Professor Yi Ma's group at UC Berkeley.
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay
PER is intuitive, this commonly used technique lacks a critical theoretical foundation.
CROCS: Clustering and Retrieval of Cardiac Signals Based on Patient Disease Class, Sex, and Age
The process of manually searching for relevant instances in, and extracting information from, clinical databases underpin a multitude of clinical tasks.
Learning to Ground Multi-Agent Communication with Autoencoders
Communication requires having a common language, a lingua franca, between agents.
Decision Transformer: Reinforcement Learning via Sequence Modeling
We introduce a framework that abstracts Reinforcement Learning (RL) as a sequence modeling problem.