Recent & Upcoming Talks

2024

The Dissimilarity Dimension: Sharper Bounds for Optimistic Algorithms.

The principle of Optimism in the Face of Uncertainty (OFU) is one of the foundational algorithmic design choices in Reinforcement …
Jan 10, 2024 12:00 AM MIT, UCSD

2023

RLHF: Reinforcement Learning with Once-per-Episode Feedback

Despite Reinforcement learning’s remarkable success in several application and simulation domains, research in the field has …
Feb 16, 2023 12:00 AM Virtual

LEARNING SYSTEMS IN ADAPTIVE ENVIRONMENTS. THEORY, ALGORITHMS AND DESIGN

February/March 2023
Feb 14, 2023 12:00 AM University of California Los Angeles, Cornell University, University College London, University of Chicago, Yale University, University of California San Diego, Brown University

2022

Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity.

Reinforcement learning provides an automated framework for learning behaviors from high-level reward specifications, but in practice …
Nov 1, 2022 12:00 AM Princeton University, University College London

On the Statistical Complexity of Batch Learning: Theory and Algorithms

In this work we develop the technique of optimism regularization, a simple way of inducing optimistic predictions in NN models. I show …
Nov 1, 2022 12:00 AM Oxford University