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» Learning the unified kernel machines for classification
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ICML
2009
IEEE
14 years 8 months ago
Learning kernels from indefinite similarities
Similarity measures in many real applications generate indefinite similarity matrices. In this paper, we consider the problem of classification based on such indefinite similariti...
Yihua Chen, Maya R. Gupta, Benjamin Recht
ICML
2005
IEEE
14 years 8 months ago
Predictive low-rank decomposition for kernel methods
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...
Francis R. Bach, Michael I. Jordan
TMM
2010
270views Management» more  TMM 2010»
13 years 2 months ago
Sequence Multi-Labeling: A Unified Video Annotation Scheme With Spatial and Temporal Context
Abstract--Automatic video annotation is a challenging yet important problem for content-based video indexing and retrieval. In most existing works, annotation is formulated as a mu...
Yuanning Li, YongHong Tian, Ling-Yu Duan, Jingjing...
MIR
2006
ACM
141views Multimedia» more  MIR 2006»
14 years 1 months ago
Mining temporal patterns of movement for video content classification
Scalable approaches to video content classification are limited by an inability to automatically generate representations of events ode abstract temporal structure. This paper pre...
Michael Fleischman, Philip DeCamp, Deb Roy
JMLR
2010
152views more  JMLR 2010»
13 years 2 months ago
The SHOGUN Machine Learning Toolbox
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Sören Sonnenburg, Gunnar Rätsch, Sebasti...