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COLT
2001
Springer
15 years 9 months ago
Geometric Bounds for Generalization in Boosting
We consider geometric conditions on a labeled data set which guarantee that boosting algorithms work well when linear classifiers are used as weak learners. We start by providing ...
Shie Mannor, Ron Meir
COLT
2000
Springer
15 years 9 months ago
Entropy Numbers of Linear Function Classes
This paper collects together a miscellany of results originally motivated by the analysis of the generalization performance of the “maximum-margin” algorithm due to Vapnik and...
Robert C. Williamson, Alex J. Smola, Bernhard Sch&...
ALT
1999
Springer
15 years 8 months ago
Extended Stochastic Complexity and Minimax Relative Loss Analysis
We are concerned with the problem of sequential prediction using a givenhypothesis class of continuously-manyprediction strategies. An e ectiveperformance measure is the minimax re...
Kenji Yamanishi
CIKM
2009
Springer
15 years 8 months ago
Classification-based resource selection
In some retrieval situations, a system must search across multiple collections. This task, referred to as federated search, occurs for example when searching a distributed index o...
Jaime Arguello, Jamie Callan, Fernando Diaz
145
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ECML
2004
Springer
15 years 8 months ago
Naive Bayesian Classifiers for Ranking
It is well-known that naive Bayes performs surprisingly well in classification, but its probability estimation is poor. In many applications, however, a ranking based on class prob...
Harry Zhang, Jiang Su