![]() ![]() You are welcome to discuss Problems with other students, but the final solutions should be completely on your own. There will be three homework assignments. Probability at the level of STAT5005 or equivalent (plus mathematical maturity). ![]() Rademacher complexity, covering number, entropy.Fisher consistency, calibrated surrogate losses.Regret or excess risk bounds, convergence rate, consistency.It will cover approaches such as parametric models, neural networks, kernel methods, SVM to tasks such as regression, classification, recommender systems, ranking, and it will focus on developing a theoretical understanding and insights of the statistical properties of learning methods. This course will provide tools to the theoretical analysis of statistical machine learning methods. “There is Nothing More Practical Than A Good Theory.” - Kurt LewinĬlassification: Fisher consistency and calibrated surrogate losses
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