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Computational Complexity of Statistical Inference

Summer Cluster in Quantum Computation

Theoretical Foundations of Computer Systems

Satisfiability: Theory, Practice, and Beyond

Registration- Theoretical Foundations: From the Early Days of Neural Networks to the Modern Deep Learning Era

Probability, Geometry, and Computation in High Dimensions

Theory of Reinforcement Learning

The Quantum Wave in Computing

Lattices: Algorithms, Complexity, and Cryptography

Amanda Coston

Amanda Coston is an Assistant Professor in the Department of Statistics at UC Berkeley. Her work considers how -- and when -- machine learning and causal inference can improve decision-making in societally high-stakes settings. Her research addresses real...