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ICMCS
2006
IEEE
121views Multimedia» more  ICMCS 2006»
16 years 1 months ago
Sampling Strategies for Active Learning in Personal Photo Retrieval
With the advent and proliferation of digital cameras and computers, the number of digital photos created and stored by consumers has grown extremely large. This created increasing...
Yi Wu, Igor Kozintsev, Jean-Yves Bouguet, Carole D...
SIGECOM
2004
ACM
135views ECommerce» more  SIGECOM 2004»
16 years 20 days ago
Applying learning algorithms to preference elicitation
We consider the parallels between the preference elicitation problem in combinatorial auctions and the problem of learning an unknown function from learning theory. We show that l...
Sébastien Lahaie, David C. Parkes
PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
15 years 11 months ago
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
Philippe Rolet, Michèle Sebag, Olivier Teyt...
SIGIR
2008
ACM
15 years 7 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff
PAKDD
2011
ACM
245views Data Mining» more  PAKDD 2011»
14 years 10 months ago
Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning
Discovering rare categories and classifying new instances of them is an important data mining issue in many fields, but fully supervised learning of a rare class classifier is pr...
Timothy M. Hospedales, Shaogang Gong, Tao Xiang