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» Second Order Approximations for Probability Models
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ICML
2010
IEEE
13 years 8 months ago
Learning the Linear Dynamical System with ASOS
We develop a new algorithm, based on EM, for learning the Linear Dynamical System model. Called the method of Approximated Second-Order Statistics (ASOS) our approach achieves dra...
James Martens
TSP
2010
13 years 2 months ago
Learning graphical models for hypothesis testing and classification
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
TSE
2010
123views more  TSE 2010»
13 years 2 months ago
Directed Explicit State-Space Search in the Generation of Counterexamples for Stochastic Model Checking
Current stochastic model checkers do not make counterexamples for property violations readily available. In this paper we apply directed explicit state space search to discrete- a...
Husain Aljazzar, Stefan Leue
CSDA
2007
94views more  CSDA 2007»
13 years 7 months ago
Some extensions of score matching
Many probabilistic models are only defined up to a normalization constant. This makes maximum likelihood estimation of the model parameters very difficult. Typically, one then h...
Aapo Hyvärinen
ISAAC
2005
Springer
127views Algorithms» more  ISAAC 2005»
14 years 28 days ago
Decision Making Based on Approximate and Smoothed Pareto Curves
Abstract. We consider bicriteria optimization problems and investigate the relationship between two standard approaches to solving them: (i) computing the Pareto curve and (ii) the...
Heiner Ackermann, Alantha Newman, Heiko Rögli...