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Tue Dec 04 03:20 PM -- 03:30 PM (PST)
Anytime Induction of Cost-sensitive Trees
Saher Esmeir · Shaul Markovitch
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Tue Dec 04 03:20 PM -- 03:30 PM (PST)
A Kernel Statistical Test of Independence
Arthur Gretton · Kenji Fukumizu · Choon Hui Teo · Le Song · Bernhard Schölkopf · Alex Smola
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Tue Dec 04 03:20 PM -- 03:30 PM (PST)
McRank: Learning to Rank Using Multiple Classification and Gradient Boosting
Ping Li · Chris J Burges · Qiang Wu
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Tue Dec 04 03:20 PM -- 03:30 PM (PST)
Classification via Minimum Incremental Coding Length (MICL)
John Wright · Yangyu Tao · Zhouchen Lin · Yi Ma · Heung-Yeung Shum
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Tue Dec 04 03:20 PM -- 03:30 PM (PST)
Random Features for Large-Scale Kernel Machines
ali rahimi · Benjamin Recht
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Tue Dec 04 03:20 PM -- 08:25 PM (PST)
Consistent Minimization of Clustering Objective Functions
Ulrike von Luxburg · Sebastien Bubeck · Stefanie S Jegelka · Michael Kaufmann
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Tue Dec 04 03:20 PM -- 03:30 PM (PST)
Iterative Non-linear Dimensionality Reduction with Manifold Sculpting
Michael S Gashler · Dan Ventura · Tony Martinez
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Tue Dec 04 03:20 PM -- 03:30 PM (PST)
Bundle Methods for Machine Learning
Alex Smola · Vishwanathan S V N · Quoc V Le
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Tue Dec 04 03:20 PM -- 03:30 PM (PST)
Boosting Algorithms for Maximizing the Soft Margin
Manfred K. Warmuth · Karen Glocer · Gunnar Rätsch