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JMLR
2006
156views more  JMLR 2006»
13 years 7 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...
KSEM
2009
Springer
14 years 1 months ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer
IDA
2009
Springer
14 years 1 months ago
Canonical Dual Approach to Binary Factor Analysis
Abstract. Binary Factor Analysis (BFA) is a typical problem of Independent Component Analysis (ICA) where the signal sources are binary. Parameter learning and model selection in B...
Ke Sun, Shikui Tu, David Yang Gao, Lei Xu
ACMSE
2010
ACM
13 years 2 months ago
Learning to rank using 1-norm regularization and convex hull reduction
The ranking problem appears in many areas of study such as customer rating, social science, economics, and information retrieval. Ranking can be formulated as a classification pro...
Xiaofei Nan, Yixin Chen, Xin Dang, Dawn Wilkins
ICMCS
2007
IEEE
146views Multimedia» more  ICMCS 2007»
14 years 1 months ago
A Max Margin Framework on Image Annotation and Multimodal Image Retrieval
This paper presents a max margin framework on image annotation and multimodal image retrieval as a structured prediction model. Following the max margin approach the image retriev...
Zhen Guo, Zhongfei Zhang, Eric P. Xing, Christos F...