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ICCV
2009
IEEE
13 years 6 months ago
Efficient multi-label ranking for multi-class learning: Application to object recognition
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...
Serhat Selcuk Bucak, Pavan Kumar Mallapragada, Ron...
JMLR
2010
161views more  JMLR 2010»
13 years 3 months ago
Empirical Bernstein Boosting
Concentration inequalities that incorporate variance information (such as Bernstein's or Bennett's inequality) are often significantly tighter than counterparts (such as...
Pannagadatta K. Shivaswamy, Tony Jebara
ECCV
2006
Springer
14 years 10 months ago
TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation
Abstract. This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned ...
Jamie Shotton, John M. Winn, Carsten Rother, Anton...
BIBE
2007
IEEE
127views Bioinformatics» more  BIBE 2007»
14 years 23 days ago
Gene Selection via Matrix Factorization
The recent development of microarray gene expression techniques have made it possible to offer phenotype classification of many diseases. However, in gene expression data analysis...
Fei Wang, Tao Li
IJHPCA
2006
125views more  IJHPCA 2006»
13 years 8 months ago
Complexity Results for Collective Communications on Heterogeneous Platforms
In this paper, we consider the communications involved in the execution of a complex application, deployed on a heterogeneous platform. Such applications extensively use macro-com...
Olivier Beaumont, Loris Marchal, Yves Robert