Online Learning and Bregman Divergences

author: Manfred K. Warmuth, Department of Computer Science, University of California Santa Cruz
published: Feb. 25, 2007,   recorded: July 2006,   views: 11707


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L 1: Introduction to Online Learning (Predicting as good as the best expert, Predicting as good as the best linear combination of experts, Additive versus multiplicative family of updates)
L 2: Bregman divergences and Loss bounds (Introduction to Bregman divergences, Relative loss bounds for the linear case, Nonlinear case & matching losses, Duality and relation to exponential families)
L 3: Extensions, interpretations, applications (Online to Batch Conversions, Prior information on the weight vector, Some applications)

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