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#49 - Meta-Gradients in RL - Dr. Tom Zahavy (DeepMind)

Machine Learning Street Talk (MLST)

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Navigating Challenges in Surrogate Models

This chapter explores the complexities of adapting non-differentiable parameters in machine learning using proxy neural networks. It discusses the advantages and limitations of surrogate models in optimizing training processes, particularly in reinforcement learning, while contrasting single and multi-lifetime learning strategies.

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