| Document Date: 2008-05-22 03:19:26
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City Helsinki / Mountain View / / Company Google / / Country Finland / Lebanon / / / Facility Amphitheatre Parkway / Columbia University / University of California / / IndustryTerm well-studied boosting algorithms / inner product / iterative algorithm / weak learning algorithm / on-line learning / greedy iterative algorithms / to other boosting algorithms / boostby-majority algorithm / learning algorithm / learning algorithms / / Movie D. 2 / / Organization Rocco A. Servedio Computer Science Department / Department of Statistics / University of California / Berkeley / Columbia University / New York / / Person Philip M. Long Google / Richard Maclin / David Opitz / / Position author / / ProgrammingLanguage D / / ProvinceOrState New York / California / / PublishedMedium Machine Learning / / Technology learning algorithm / well-studied boosting algorithms / Boost-ByMajority algorithm / boostby-majority algorithm / Improved boosting algorithms / known boosting algorithms / weak learning algorithm / MadaBoost algorithm / Boosting algorithms / boosting algorithm / LogitBoost algorithm / greedy iterative algorithms / iterative algorithm / Machine Learning / corresponding Bφ algorithms / AdaBoost algorithm / Bφ algorithm / /
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Random Classification Noise Defeats All Convex Potential Boosters Philip M. Long Google, 1600 Amphitheatre Parkway, Mountain View, CA[removed]Rocco A. Servedio Computer Science Department, Columbia University, New York, NY