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- California Institute of TechnologyUS534 papers
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5 papers · 2 filters
One Permutation Hashing for Efficient Search and Learning
Ping Li, Art Owen, Cun-Hui Zhang
Recently, the method of b-bit minwise hashing has been applied to large-scale linear learning and sublinear time near-neighbor search. The major drawback of minwise hashing is the…
Obtaining Calibrated Probabilities from Boosting
Alexandru Niculescu-Mizil, Richard A. Caruana
Boosted decision trees typically yield good accuracy, precision, and ROC area. However, because the outputs from boosting are not well calibrated posterior probabilities, boosting…
Learning Object Arrangements in 3D Scenes using Human Context
Yun Jiang, Marcus Lim, Ashutosh Saxena
We consider the problem of learning object arrangements in a 3D scene. The key idea here is to learn how objects relate to human poses based on their affordances, ease of use and r…
Approximating Higher-Order Distances Using Random Projections
Ping Li, Michael W. Mahoney, Yiyuan She
We provide a simple method and relevant theoretical analysis for efficiently estimating higher-order lp distances. While the analysis mainly focuses on l4, our methodology extends…
Robust LogitBoost and Adaptive Base Class (ABC) LogitBoost
Ping Li
Logitboost is an influential boosting algorithm for classification. In this paper, we develop robust logitboost to provide an explicit formulation of tree-split criterion for build…