Effect Handlers and Choice-Based Learning in JAX
Abstract
Choice-based learning is a programming paradigm for expressing learning system in terms of choices and losses. We explore a practical implementation of choice-based learning in JAX by combining two techniques in a novel way: algebraic effects and the selection monad. We describe the design and implementation of our library, explore its usefulness for real-world applications like hyperparameter tuning and deep reinforcement learning, and compare it with existing approaches.
Research Areas
