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» On Learning Boolean Functions
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WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
14 years 2 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...
ECCV
2008
Springer
16 years 8 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
RECOMB
2009
Springer
16 years 7 months ago
Learning Models for Aligning Protein Sequences with Predicted Secondary Structure
Accurately aligning distant protein sequences is notoriously difficult. A recent approach to improving alignment accuracy is to use additional information such as predicted seconda...
Eagu Kim, Travis J. Wheeler, John D. Kececioglu
219
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KSEM
2009
Springer
16 years 1 months ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer
ATAL
2007
Springer
16 years 26 days ago
Sharing experiences to learn user characteristics in dynamic environments with sparse data
This paper investigates the problem of estimating the value of probabilistic parameters needed for decision making in environments in which an agent, operating within a multi-agen...
David Sarne, Barbara J. Grosz