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Workshop: Machine Learning for Systems

Choice-Based Learning in JAX

Daniel Zheng · Shangyin Tan · Gordon Plotkin · Ningning Xie


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.

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