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NIPS 2009 Workshop, Hilton Whistler Resort: Diamond Head, Saturday, December 12, 2009 Call for Abstracts Format Speakers References Motivation and Goals Permutations and partial orders as input and output data are ubiquitous. Examples include: Preference elicitation Social choice and voting theory Ranking and search. Tracking and identity management Structure learning for Bayesian networks Mul
Beyond Convexity: Submodularity in Machine Learning Description Convex optimization has become a main workhorse for many machine learning algorithms during the past ten years. When minimizing a convex loss function for, e.g., training a Support Vector Machine, we can rest assured to efficiently find an optimal solution, even for large problems. In recent years, another fundamental problem st
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