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» Training Linear Discriminant Analysis in Linear Time
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STOC
1996
ACM
115views Algorithms» more  STOC 1996»
15 years 4 months ago
Minimum Cuts in Near-Linear Time
We significantly improve known time bounds for solving the minimum cut problem on undirected graphs. We use a "semiduality" between minimum cuts and maximum spanning tree...
David R. Karger
ICDM
2009
IEEE
174views Data Mining» more  ICDM 2009»
15 years 6 months ago
Non-sparse Multiple Kernel Learning for Fisher Discriminant Analysis
—We consider the problem of learning a linear combination of pre-specified kernel matrices in the Fisher discriminant analysis setting. Existing methods for such a task impose a...
Fei Yan, Josef Kittler, Krystian Mikolajczyk, Muha...
SPEECH
1998
171views more  SPEECH 1998»
14 years 11 months ago
Heteroscedastic discriminant analysis and reduced rank HMMs for improved speech recognition
We present the theory for heteroscedastic discriminant analysis (HDA), a model-based generalization of linear discriminant analysis (LDA) derived in the maximum-likelihood framewo...
Nagendra Kumar, Andreas G. Andreou
BMVC
2001
15 years 2 months ago
Recognising Trajectories of Facial Identities Using Kernel Discriminant Analysis
We present a comprehensive approach to address three challenging problems in face recognition: modelling faces across multi-views, extracting the non-linear discriminating feature...
Yongmin Li, Shaogang Gong, Heather M. Liddell
ICCV
2009
IEEE
16 years 4 months ago
Max-Margin Additive Classifiers for Detection
We present methods for training high quality object detectors very quickly. The core contribution is a pair of fast training algorithms for piece-wise linear classifiers, which ...
Subhransu Maji, Alexander C. Berg