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» A New Discriminative Kernel From Probabilistic Models
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KDD
2008
ACM
178views Data Mining» more  KDD 2008»
15 years 10 months ago
Training structural svms with kernels using sampled cuts
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
Chun-Nam John Yu, Thorsten Joachims
ICIP
2009
IEEE
14 years 7 months ago
Object tracking by bidirectional learning with feature selection
This paper proposes a new tracking algorithm which combines object and background information, via building object and background appearance models simultaneously by nonparametric...
Heng Wang, Xinwen Hou, Cheng-Lin Liu
PAMI
2008
162views more  PAMI 2008»
14 years 9 months ago
Dimensionality Reduction of Clustered Data Sets
We present a novel probabilistic latent variable model to perform linear dimensionality reduction on data sets which contain clusters. We prove that the maximum likelihood solution...
Guido Sanguinetti
CVPR
1998
IEEE
15 years 11 months ago
A Methodology for Deriving Probabilistic Correctness Measures from Recognizers
This paper describes the derivation of probability of correctness from scores assigned by most recognizers. Motivation for this research is three-fold: i probability values can be...
Djamel Bouchaffra, Venu Govindaraju, Sargur N. Sri...
CVPR
2012
IEEE
13 years 6 days ago
Supervised hashing with kernels
Recent years have witnessed the growing popularity of hashing in large-scale vision problems. It has been shown that the hashing quality could be boosted by leveraging supervised ...
Wei Liu, Jun Wang, Rongrong Ji, Yu-Gang Jiang, Shi...