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MA
2010
Springer
94views Communications» more  MA 2010»
13 years 8 months ago
On sparse estimation for semiparametric linear transformation models
: Semiparametric linear transformation models have received much attention due to its high flexibility in modeling survival data. A useful estimating equation procedure was recent...
Hao Helen Zhang, Wenbin Lu, Hansheng Wang
ICMCS
2008
IEEE
151views Multimedia» more  ICMCS 2008»
14 years 4 months ago
Fast keyword detection with sparse time-frequency models
We address the problem of keyword spotting in continuous speech streams when training and testing conditions can be different. We propose a keyword spotting algorithm based on spa...
Effrosini Kokiopoulou, Pascal Frossard, Olivier Ve...
ECCV
2008
Springer
14 years 11 months ago
Discriminative Sparse Image Models for Class-Specific Edge Detection and Image Interpretation
Abstract. Sparse signal models learned from data are widely used in audio, image, and video restoration. They have recently been generalized to discriminative image understanding t...
Julien Mairal, Marius Leordeanu, Francis Bach, Mar...
CVPR
2010
IEEE
13 years 10 months 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
BRAIN
2010
Springer
13 years 8 months ago
Sparse Regression Models of Pain Perception
Discovering brain mechanisms underlying pain perception remains a challenging neuroscientific problem with important practical applications, such as developing better treatments f...
Irina Rish, Guillermo A. Cecchi, Marwan N. Baliki,...