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» Nonrigid Embeddings for Dimensionality Reduction
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ICMCS
2006
IEEE
161views Multimedia» more  ICMCS 2006»
15 years 3 months ago
Emotion Recognition from Noisy Speech
This paper presents an emotion recognition system from clean and noisy speech. Geodesic distance was adopted to preserve the intrinsic geometry of emotional speech. Based on the g...
Mingyu You, Chun Chen, Jiajun Bu, Jia Liu, Jianhua...
81
Voted
CVPR
2004
IEEE
15 years 1 months ago
Visual Object Categorization Using Distance-Based Discriminant Analysis
This paper formulates the problem of object categorization in the discriminant analysis framework focusing on transforming visual feature data so as to make it conform to the comp...
Serhiy Kosinov, Stéphane Marchand-Maillet, ...
PAMI
2008
391views more  PAMI 2008»
14 years 9 months ago
Riemannian Manifold Learning
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
Tong Lin, Hongbin Zha
BMCBI
2005
80views more  BMCBI 2005»
14 years 9 months ago
Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm
Background: Life processes are determined by the organism's genetic profile and multiple environmental variables. However the interaction between these factors is inherently ...
Kevin Dawson, Raymond L. Rodriguez, Wasyl Malyj
PR
2007
88views more  PR 2007»
14 years 9 months ago
Robust kernel Isomap
Isomap is one of widely-used low-dimensional embedding methods, where geodesic distances on a weighted graph are incorporated with the classical scaling (metric multidimensional s...
Heeyoul Choi, Seungjin Choi