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CVPR
2010
IEEE
15 years 2 days ago
Robust RVM regression using sparse outlier model
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
ICASSP
2010
IEEE
15 years 2 days ago
Sparse Bayesian step-filtering for high-throughput analysis of molecular machine dynamics
Nature has evolved many molecular machines such as kinesin, myosin, and the rotary flagellar motor powered by an ion current from the mitochondria. Direct observation of the step-...
Max A. Little, Nick S. Jones
ICASSP
2010
IEEE
14 years 9 months ago
Speech enhancement with sparse coding in learned dictionaries
The enhancement of speech degraded by non-stationary interferers is a highly relevant and difficult task of many signal processing applications. We present a monaural speech enhan...
Christian D. Sigg, Tomas Dikk, Joachim M. Buhmann
PKDD
2010
Springer
169views Data Mining» more  PKDD 2010»
14 years 9 months ago
Efficient and Numerically Stable Sparse Learning
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Sihong Xie, Wei Fan, Olivier Verscheure, Jiangtao ...
PRICAI
2010
Springer
14 years 9 months ago
Sparse Representation: Extract Adaptive Neighborhood for Multilabel Classification
Unlike traditional classification tasks, multilabel classification allows a sample to associate with more than one label. This generalization naturally arises the difficulty in cla...
Shuo Xiang, Songcan Chen, Lishan Qiao