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NECO
2010
97views more  NECO 2010»
13 years 7 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
JMLR
2006
389views more  JMLR 2006»
13 years 8 months ago
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Enrique Castillo, Bertha Guijarro-Berdiñas,...
ESANN
2001
13 years 10 months ago
Learning fault-tolerance in Radial Basis Function Networks
This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...
Xavier Parra, Andreu Català
ICASSP
2011
IEEE
13 years 15 days ago
Error compensation and reliability based view synthesis
View synthesis offers a great flexibility in generating free viewpoint television (FTV) and 3D video (3DV). However, the depth-image-based view synthesis approach is very sensiti...
Wenxiu Sun, Oscar C. Au, Lingfeng Xu, Sung Him Chu...
DMIN
2006
125views Data Mining» more  DMIN 2006»
13 years 10 months ago
Privacy-Preserving Bayesian Network Learning From Heterogeneous Distributed Data
In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...
Jianjie Ma, Krishnamoorthy Sivakumar