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NIPS
2000
13 years 8 months ago
High-temperature Expansions for Learning Models of Nonnegative Data
Recent work has exploited boundedness of data in the unsupervised learning of new types of generative model. For nonnegative data it was recently shown that the maximum-entropy ge...
Oliver B. Downs
KDD
2007
ACM
152views Data Mining» more  KDD 2007»
14 years 7 months ago
A framework for classification and segmentation of massive audio data streams
In recent years, the proliferation of VOIP data has created a number of applications in which it is desirable to perform quick online classification and recognition of massive voi...
Charu C. Aggarwal
ICDM
2008
IEEE
160views Data Mining» more  ICDM 2008»
14 years 1 months ago
Direct Zero-Norm Optimization for Feature Selection
Zero-norm, defined as the number of non-zero elements in a vector, is an ideal quantity for feature selection. However, minimization of zero-norm is generally regarded as a combi...
Kaizhu Huang, Irwin King, Michael R. Lyu
ICASSP
2009
IEEE
13 years 4 months ago
Weighted nonnegative matrix factorization
Nonnegative matrix factorization (NMF) is a widely-used method for low-rank approximation (LRA) of a nonnegative matrix (matrix with only nonnegative entries), where nonnegativity...
Yong-Deok Kim, Seungjin Choi
ICIP
2007
IEEE
14 years 8 months ago
A Statistical Approach for Intensity Loss Compensation of Confocal Microscopy Images
In this paper a probabilistic technique for compensation of intensity loss in the confocal microscopy images is presented. Confocal microscopy images are modeled as a mixture of t...
Sowmya Gopinath, Ninad Thakoor, Jean Gao, Kate Lub...