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» A Training Method with Small Computation for Classification
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SEMCO
2007
IEEE
14 years 2 months ago
Large-Margin Discriminative Training of Hidden Markov Models for Speech Recognition
Discriminative training has been a leading factor for improving automatic speech recognition (ASR) performance over the last decade. The traditional discriminative training, howev...
Dong Yu, Li Deng
CVPR
2005
IEEE
14 years 10 months ago
Representational Oriented Component Analysis (ROCA) for Face Recognition with One Sample Image per Training Class
Subspace methods such as PCA, LDA, ICA have become a standard tool to perform visual learning and recognition. In this paper we propose Representational Oriented Component Analysi...
Fernando De la Torre, Ralph Gross, Simon Baker, B....
ICPR
2006
IEEE
14 years 9 months ago
Enhancing Training Set for Face Detection
We present a novel method to enhance training set for face detection with nonlinearly generated examples from the original data. The motivation is from Support Vector Machines (SV...
Ruiping Wang, Jie Chen, Shiguang Shan, Wen Gao
ICCS
2004
Springer
14 years 1 months ago
Chunking-Coordinated-Synthetic Approaches to Large-Scale Kernel Machines
We consider a kernel-based approach to nonlinear classification that coordinates the generation of “synthetic” points (to be used in the kernel) with “chunking” (working wi...
Francisco J. González-Castaño, Rober...
CVPR
2007
IEEE
14 years 10 months ago
Face Recognition using Discriminatively Trained Orthogonal Rank One Tensor Projections
We propose a method for face recognition based on a discriminative linear projection. In this formulation images are treated as tensors, rather than the more conventional vector o...
Gang Hua, Paul A. Viola, Steven M. Drucker