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JMLR 2010
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Negative Results for Active Learning with Convex Losses
13 years 6 months ago
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www.cs.cmu.edu
We study the problem of active learning with convex loss functions. We prove that even under bounded noise constraints, the minimax rates for proper active learning are often no better than passive learning.
Steve Hanneke, Liu Yang
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Convex Loss Functions
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JMLR 2010
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Passive Learning
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Proper Active Learning
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Added
19 May 2011
Updated
19 May 2011
Type
Journal
Year
2010
Where
JMLR
Authors
Steve Hanneke, Liu Yang
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Researcher Info
JMLR 2000 Study Group
Computer Vision