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WSC
1997
14 years 11 months ago
Selecting the Best System: A Decision-Theoretic Approach
The problem of selecting the best system from a finite set of alternatives is considered from a Bayesian decision-theoretic perspective. The framework presented is quite general,...
Stephen E. Chick
NIPS
2007
14 years 11 months ago
Bayesian Co-Training
We propose a Bayesian undirected graphical model for co-training, or more generally for semi-supervised multi-view learning. This makes explicit the previously unstated assumption...
Shipeng Yu, Balaji Krishnapuram, Rómer Rosa...
NIPS
1997
14 years 11 months ago
Nonlinear Markov Networks for Continuous Variables
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
Reimar Hofmann, Volker Tresp
SIAMJO
2010
128views more  SIAMJO 2010»
14 years 4 months ago
Solving Log-Determinant Optimization Problems by a Newton-CG Primal Proximal Point Algorithm
We propose a Newton-CG primal proximal point algorithm for solving large scale log-determinant optimization problems. Our algorithm employs the essential ideas of the proximal poi...
Chengjing Wang, Defeng Sun, Kim-Chuan Toh
DIS
2007
Springer
15 years 3 months ago
A Hilbert Space Embedding for Distributions
We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a reprodu...
Alexander J. Smola, Arthur Gretton, Le Song, Bernh...