See this document in CiteSeerX!

Probabilistic Kernel Matrix Learning with a Mixture Model of Kernels  (Make Corrections)  
Zhihua Zhang, Dit-Yan Yeung, and James T. Kwok



  Home/Search   Context   Related

 
View or download:
cs.ust.hk/~zhzhang/pape...paper0803.pdf
Cached:  PS.gz  PS  PDF   Image  Update  Help

From:  cs.ust.hk/~zhzhang/all (more)
(Enter author homepages)

Rate this article: (best)
  Comment on this article  
(Enter summary)

Abstract: This paper addresses the kernel matrix learning problem in kernel methods. We model the kernel matrix as a random positive definite matrix following the Wishart distribution, with the parameter matrix of the Wishart distribution represented as a linear combination of mutually independent matrices with their own Wishart distributions. This defines a probabilistic mixture model of kernels that can be represented as a hierarchical model involving three levels, relating the target kernel... (Update)

Active bibliography (related documents):   More   All
1.3:   Wishart Processes: A Statistical View of Reproducing.. - Zhang, Yeung, Kwok (2004)   (Correct)
0.5:   Hyperkernels - Ong, Smola, Williamson   (Correct)
0.3:   On the Complexity of Learning - The Kernel Matrix   (Correct)

Similar documents based on text:   More   All
0.4:   Wishart Processes: A Statistical View of Reproducing Kernels - Zhang, Yeung, Kwok (2004)   (Correct)
0.4:   Bayesian Inference for Transductive Learning of Kernel.. - Zhang, Yeung, Kwok   (Correct)
0.4:   Bayesian Transductive Learning of the Kernel Matrix - Zhihua Zhang Zhzhang   (Correct)

BibTeX entry:   (Update)

@misc{ zhang-probabilistic,
  author = "Zhihua Zhang and Dit-Yan Yeung and and James T. Kwok",
  title = "Probabilistic Kernel Matrix Learning with a Mixture Model of Kernels",
  url = "citeseer.ist.psu.edu/704161.html" }
Citations (may not include all citations):
2528   Maximum likelihood from incomplete data via the EM algorithm (context) - Dempster, Laird et al. - 1977
947   Statistical Learning Theory (context) - Vapnik - 1998
574   Pattern Classification (context) - Duda, Hart et al. - 2001
524   Support-vector networks - Cortes, Vapnik - 1995
326   Topics in Matrix Analysis (context) - Horn, Johnson - 1991
226   The EM Algorithm and Extensions (context) - McLachlan, Krishnan - 1997
187   Nonlinear component analysis as a kernel eigenvalue problem (context) - Scholkopf, Smola et al. - 1998
173   The calculation of posterior distributions by data augmentat.. (context) - Tanner, Wong - 1987
113   Learning with Kernels (context) - Scholkopf, Smola - 2002
71   Finite Mixture Models (context) - McLachlan, Peel - 2000
62   Information geometry of the EM and em algorithms for neural .. - Amari - 1995
43   Transactions of the American Mathematical Society (context) - Aronszajn, reeproducing - 1950
38   Choosing multiple parameters for support vector machines - Chapelle, Vapnik et al. - 2002
28   Learning the kernel matrix with semi-definite programming - Lanckriet, Cristianini et al. - 2002
24   Generalized discriminant analysis using a kernel approach - Baudat, Anouar - 2000
19   On kernel target alignment - Cristianini, Kandola et al. - 2002
15   Matrix Variate Distributions (context) - Gupta, Nagar - 2000
11   The evidence framework applied to support vector machines - Kwok - 2000
8   the complexity of learning the kernel matrix (context) - Bousquet, Herrmann - 2003
3   Kernel design using boosting - Crammer, Keshet et al. - 2003
3   Optimizing kernel alignment over combinations of kernels (context) - Kandola, Shawe-Taylor et al. - 2002
3   The em algorithm for kernel matrix completion with auxiliary.. (context) - Tsuda, Akaho et al. - 2003
1   Refining kernels for regression and uneven classification pr.. - Kandola, Shawe-Taylor - 2003
1   On approximating a linear combination of central Wishart mat.. (context) - Tan, Gupta - 1983
1   Multivariate generalization of t'-statistics based on the me.. (context) - Khatri - 1983
1   and Bayesian inference by the Tanner-Wong algorithm (context) - Zhang, Yeung et al. - 2003
1   Machine learning with hyperkernels (context) - Ong, Smola - 2003
1   Probabilistic kernel matrix learning (context) - Zhang, Yeung et al. - 2003

Documents on the same site (http://www.cs.ust.hk/~zhzhang/all.htm):   More
EM algorithms for Gaussian mixtures with split-and-merge.. - Zhang, Chen, Sun, Chan (2003)   (Correct)
Bayesian Inference on Principal Component Analysis Using .. - Zhang, Chan, Kwok, Yeung   (Correct)
Convexity, Surrogate Functions and Iterative.. - Zhang, Kwok, Yeung, Wang   (Correct)

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC