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City New York / / Company IBM / Neural Information Processing Systems / MIT Press / John Wiley and Sons / Sun / AAAI/MIT Press / ACM Press / Baxter / / / Facility Boosting Philip M. Long Genome Institute of Singapore / Sequoia Hall / University of Chicago / / IndustryTerm minimum majority algorithm / classification algorithm / good algorithms / integer solutions / feasible solution / on-line prediction / weak learning algorithm / greedy algorithm / linear-threshold algorithm / on-line learning / fractional solution / integer solution / randomized rounding algorithm / basic algorithm / polynomialtime algorithm / learning algorithm / approximation algorithms / learning algorithms / / MarketIndex SET 100 / / Organization Artifical Intelligence / The University of Chicago / MIT / Department of Statistics / Minimum Majority Classification and Boosting Philip M. Long Genome Institute of Singapore / Artifiicial Intelligence / / Person Schapire / Stanford Univerity / Williamson / Philip M. Long / / Position author / Singer / / ProgrammingLanguage Occam / / ProvinceOrState New York / / PublishedMedium Machine Learning / / Technology Logarithmic Linear-threshold Learning Algorithms / learning algorithm / Natural Language Processing / Knowledge Management / minimum majority algorithm / artificial intelligence / weak learning algorithm / Boosting algorithms / linear-threshold algorithm / alternative algorithm / Introduction Boosting algorithms / boosting algorithm / provably good algorithms / randomized rounding algorithm / greedy algorithm / approximation algorithms / voting classification algorithm / machine learning / polynomialtime algorithm / basic algorithm / / URL www.aaai.org / http / SocialTag 
Minimum Majority Classification and Boosting Philip M. Long Genome Institute of Singapore 1 Science Park Road The Capricorn, #05-01 Singapore[removed], Republic of Singapore