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» Generalization Bounds for Learning Kernels
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FOCS
2008
IEEE
14 years 3 months ago
Submodular Approximation: Sampling-based Algorithms and Lower Bounds
We introduce several generalizations of classical computer science problems obtained by replacing simpler objective functions with general submodular functions. The new problems i...
Zoya Svitkina, Lisa Fleischer
ECML
2005
Springer
14 years 2 months ago
Kernel Basis Pursuit
ABSTRACT. Estimating a non-uniformly sampled function from a set of learning points is a classical regression problem. Kernel methods have been widely used in this context, but eve...
Vincent Guigue, Alain Rakotomamonjy, Stépha...
CIKM
2009
Springer
14 years 3 months ago
L2 norm regularized feature kernel regression for graph data
Features in many real world applications such as Cheminformatics, Bioinformatics and Information Retrieval have complex internal structure. For example, frequent patterns mined fr...
Hongliang Fei, Jun Huan
TASLP
2011
13 years 3 months ago
Predicting Preference Judgments of Individual Normal and Hearing-Impaired Listeners With Gaussian Processes
Abstract—A probabilistic kernel approach to pairwise preference learning based on Gaussian processes is applied to predict preference judgments for sound quality degradation mech...
Perry Groot, Tom Heskes, Tjeerd Dijkstra, James M....
SDM
2007
SIAM
81views Data Mining» more  SDM 2007»
13 years 10 months ago
A PAC Bound for Approximate Support Vector Machines
We study a class of algorithms that speed up the training process of support vector machines (SVMs) by returning an approximate SVM. We focus on algorithms that reduce the size of...
Dongwei Cao, Daniel Boley