Logarithmic Regret for Online Control with Adversarial Noise

no code implementations • ICML 2020 • Dylan Foster, Max Simchowitz

We consider the problem of online control in a known linear dynamical system subject to adversarial noise.

LEMMA

Improved Bounds on Minimax Regret under Logarithmic Loss via Self-Concordance

no code implementations • ICML 2020 • Blair Bilodeau, Dylan Foster, Daniel Roy

We study the classical problem of forecasting under logarithmic loss while competing against an arbitrary class of experts.

Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models

no code implementations • 17 Jul 2022 • Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Didolkar, Dipendra Misra, Dylan Foster, Lekan Molu, Rajan Chari, Akshay Krishnamurthy, John Langford

In many sequential decision-making tasks, the agent is not able to model the full complexity of the world, which consists of multitudes of relevant and irrelevant information.

Decision Making