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Exploring Causal Discovery in Machine Learning
This chapter examines the principles of causal discovery, emphasizing its role as a continuous optimization problem through directed acyclic graphs. It discusses the practical implications of causal relationships in fields like drug discovery and recent advancements in learning mechanisms for machine learning systems.