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Stochastic Optimization for Machine Learning ICML 2010, Haifa, Israel Tutorial by Nati Srebro and Ambuj Tewari Toyota Technological Institute at Chicago Goals • Introduce Stochastic Optimization setup, and its relationship to Statistical Learning and Online Learning • Understand Stochastic Gradient Descent: formulation, analysis and use in machine learning • Learn about extensions and generalizati

Stochastic Optimization: ICML 2010 Tutorial Nathan Srebro and Ambuj Tewari Topic Overview Stochastic Optimization played an important role in Machine Learning in the past, and is lately again playing an increasingly important role, both as a conceptual framework and as a computational tool. This is not at all surprising. First, the standard Statistical Learning setups, e.g. the (agnostic) PAC Fram