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» Lower Bounds for Agnostic Learning via Approximate Rank
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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 11 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
FOCS
2008
IEEE
13 years 11 months ago
Learning Geometric Concepts via Gaussian Surface Area
We study the learnability of sets in Rn under the Gaussian distribution, taking Gaussian surface area as the “complexity measure” of the sets being learned. Let CS denote the ...
Adam R. Klivans, Ryan O'Donnell, Rocco A. Servedio
JMLR
2006
117views more  JMLR 2006»
13 years 4 months ago
On the Complexity of Learning Lexicographic Strategies
Fast and frugal heuristics are well studied models of bounded rationality. Psychological research has proposed the take-the-best heuristic as a successful strategy in decision mak...
Michael Schmitt, Laura Martignon
ADC
2006
Springer
136views Database» more  ADC 2006»
13 years 10 months ago
A multi-step strategy for approximate similarity search in image databases
Many strategies for similarity search in image databases assume a metric and quadratic form-based similarity model where an optimal lower bounding distance function exists for fil...
Paul Wing Hing Kwan, Junbin Gao