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» Introduction to Statistical Learning Theory
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SYNTHESE
2008
84views more  SYNTHESE 2008»
13 years 7 months ago
How experimental algorithmics can benefit from Mayo's extensions to Neyman-Pearson theory of testing
Although theoretical results for several algorithms in many application domains were presented during the last decades, not all algorithms can be analyzed fully theoretically. Exp...
Thomas Bartz-Beielstein
ISCAS
1994
IEEE
131views Hardware» more  ISCAS 1994»
13 years 11 months ago
An Efficient Design Method for Optimal Weighted Median Filtering
Earlier research has shown that the problem of optimal weighted median filtering with structural constraints can be formulated as a nonconvex nonlinear programming problem in gene...
Ruikang Yang, Moncef Gabbouj, Yrjö Neuvo
STOC
2000
ACM
174views Algorithms» more  STOC 2000»
13 years 11 months ago
Noise-tolerant learning, the parity problem, and the statistical query model
We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
Avrim Blum, Adam Kalai, Hal Wasserman
NC
2002
196views Neural Networks» more  NC 2002»
13 years 7 months ago
Beyond second-order statistics for learning: A pairwise interaction model for entropy estimation
Second order statistics have formed the basis of learning and adaptation due to its appeal and analytical simplicity. On the other hand, in many realistic engineering problems requ...
Deniz Erdogmus, José Carlos Príncipe...
NIPS
2007
13 years 9 months ago
Statistical Analysis of Semi-Supervised Regression
Semi-supervised methods use unlabeled data in addition to labeled data to construct predictors. While existing semi-supervised methods have shown some promising empirical performa...
John D. Lafferty, Larry A. Wasserman