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NECO
2010
97views more  NECO 2010»
13 years 6 months ago
Rademacher Chaos Complexities for Learning the Kernel Problem
In this paper we develop a novel generalization bound for learning the kernel problem. First, we show that the generalization analysis of the kernel learning problem reduces to in...
Yiming Ying, Colin Campbell
ACCV
2006
Springer
13 years 11 months ago
Multiple Similarities Based Kernel Subspace Learning for Image Classification
Abstract. In this paper, we propose a new method for image classification, in which matrix based kernel features are designed to capture the multiple similarities between images in...
Wang Yan, Qingshan Liu, Hanqing Lu, Songde Ma
EACL
2006
ACL Anthology
13 years 9 months ago
Making Tree Kernels Practical for Natural Language Learning
In recent years tree kernels have been proposed for the automatic learning of natural language applications. Unfortunately, they show (a) an inherent super linear complexity and (...
Alessandro Moschitti
JMLR
2010
132views more  JMLR 2010»
13 years 2 months ago
On the Impact of Kernel Approximation on Learning Accuracy
Kernel approximation is commonly used to scale kernel-based algorithms to applications containing as many as several million instances. This paper analyzes the effect of such appr...
Corinna Cortes, Mehryar Mohri, Ameet Talwalkar
ICASSP
2011
IEEE
12 years 11 months ago
Speaker recognition using multiple kernel learning based on conditional entropy minimization
We applied a multiple kernel learning (MKL) method based on information-theoretic optimization to speaker recognition. Most of the kernel methods applied to speaker recognition sy...
Tetsuji Ogawa, Hideitsu Hino, Nima Reyhani, Noboru...