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ICASSP
2011
IEEE
8 years 2 days ago
A kernelized maximal-figure-of-merit learning approach based on subspace distance minimization
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
Byungki Byun, Chin-Hui Lee
TSP
2008
113views more  TSP 2008»
8 years 8 months ago
Covariance Matrix Estimation With Heterogeneous Samples
We consider the problem of estimating the covariance matrix of an observation vector, using heterogeneous training samples, i.e., samples whose covariance matrices are not exactly ...
Olivier Besson, Stéphanie Bidon, Jean-Yves ...
TNN
2008
105views more  TNN 2008»
8 years 8 months ago
Incremental Learning of Chunk Data for Online Pattern Classification Systems
This paper presents a pattern classification system in which feature extraction and classifier learning are simultaneously carried out not only online but also in one pass where tr...
Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov
TNN
2008
97views more  TNN 2008»
8 years 8 months ago
Training Hard-Margin Support Vector Machines Using Greedy Stagewise Algorithm
Hard-margin support vector machines (HM-SVMs) suffer from getting overfitting in the presence of noise. Soft-margin SVMs deal with this problem by introducing a regularization term...
Liefeng Bo, Ling Wang, Licheng Jiao
CVPR
2008
IEEE
8 years 8 months ago
Robust learning of discriminative projection for multicategory classification on the Stiefel manifold
Learning a robust projection with a small number of training samples is still a challenging problem in face recognition, especially when the unseen faces have extreme variation in...
Duc-Son Pham, Svetha Venkatesh
ICONIP
2008
8 years 9 months ago
Experimental Study of Ergodic Learning Curve in Hidden Markov Models
A number of learning machines used in information science are not regular, but rather singular, because they are non-identifiable and their Fisher information matrices are singula...
Masashi Matsumoto, Sumio Watanabe
ICMLA
2008
8 years 9 months ago
Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins
In this paper, we introduce two new formulations for multi-class multi-kernel relevance vector machines (mRVMs) that explicitly lead to sparse solutions, both in samples and in nu...
Theodoros Damoulas, Yiming Ying, Mark A. Girolami,...
AAAI
2007
8 years 10 months ago
Learning by Combining Observations and User Edits
We introduce a new collaborative machine learning paradigm in which the user directs a learning algorithm by manually editing the automatically induced model. We identify a generi...
Vittorio Castelli, Lawrence D. Bergman, Daniel Obl...
DRR
2010
8 years 10 months ago
Time and space optimization of document content classifiers
Scaling up document-image classifiers to handle an unlimited variety of document and image types poses serious challenges to conventional trainable classifier technologies. Highly...
Dawei Yin, Henry S. Baird, Chang An
CSB
2004
IEEE
135views Bioinformatics» more  CSB 2004»
9 years 2 days ago
Selection of Patient Samples and Genes for Outcome Prediction
Gene expression profiles with clinical outcome data enable monitoring of disease progression and prediction of patient survival at the molecular level. We present a new computatio...
Huiqing Liu, Jinyan Li, Limsoon Wong
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