Bayesian Machine Learning and Information Processing (Fall 2020)
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Data Systems for Machine Learning (Fall 2020)
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COS 302: Mathematics for Numerical Computing and Machine Learning (Fall 2020)
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Advanced Topics in Quantum Information Theory (Fall 2020)
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Machine Learning (Fall 2019)
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Probability and Info Theory in Machine Learning (Fall 2020)
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Introduction to Quantum Information Science (Fall 2020)
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Multivariate Statistics and Machine Learning (Fall 2020)
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Thermodynamics (Fall 2020)
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Speech Processing (Fall 2021)
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Introduction to Graph Theory (Fall 2020)
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Matrix Calculus For Machine Learning And Beyond (IAP 2023)
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Multimedia Signal Processing (Fall 2020)
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Graph Theory (Fall 2020)
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General Topology (Fall 2020)
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Adaptive Control and Reinforcement Learning (Fall 2020)
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Machine Learning (Fall 2016)
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Data Science and Machine Learning (Spring 2021)
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Introduction to Lie Groups (Fall 2020)（部分）
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Optimization for AI (Fall 2020)
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Advanced Topics in the Theory of Machine Learning (Spring 2021)
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Introduction to Information Theory (Fall 2019)
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Matrix Theory (Fall 2020)
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Concentration Inequalities and Model Selection (Fall 2020)
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Fundamentals of Signals and Systems (Fall 2020)
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Calculus on Manifolds (Fall 2020)
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Nonlinear Optimization (Fall 2020)
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Simulating Stochastic Systems (Fall 2020)
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Mathematical Methods in Signal Processing (Fall 2017)
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Measure Theory (Fall 2020)
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Optimization in Machine Learning (Spring 2021)
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Mathematical Computer Graphics (Fall 2020)
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Energy Methods and Computational Mechanics (Fall 2020)
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Fundamental Mathematics (Fall 2020)
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Analysis, Random Walks and Groups (Fall 2020)
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Art History (Fall 2020)
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Quantum Physics for Non-Physicists (Fall 2020)
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Martingale Theory with Applications (Fall 2020)
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Tensor Computations (Fall 2020)
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Introduction to Game Development (Fall 2020)
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Principles of Statistics (Fall 2020)