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» A bound on the label complexity of agnostic active learning
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CC
2010
Springer
120views System Software» more  CC 2010»
13 years 2 months ago
Lower Bounds for Agnostic Learning via Approximate Rank
We prove that the concept class of disjunctions cannot be pointwise approximated by linear combinations of any small set of arbitrary real-valued functions. That is, suppose that t...
Adam R. Klivans, Alexander A. Sherstov
COLT
2007
Springer
13 years 10 months ago
A Lower Bound for Agnostically Learning Disjunctions
We prove that the concept class of disjunctions cannot be pointwise approximated by linear combinations of any small set of arbitrary real-valued functions. That is, suppose there ...
Adam R. Klivans, Alexander A. Sherstov
ALT
2006
Springer
14 years 1 months ago
Active Learning in the Non-realizable Case
Most of the existing active learning algorithms are based on the realizability assumption: The learner’s hypothesis class is assumed to contain a target function that perfectly c...
Matti Kääriäinen
ALT
2002
Springer
14 years 1 months ago
Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning
We describe a new boosting algorithm that is the first such algorithm to be both smooth and adaptive. These two features make possible performance improvements for many learning ...
Dmitry Gavinsky
IJCNN
2007
IEEE
13 years 11 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot