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» A New Practically Efficient Interior Point Method for LP
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UAI
2008
13 years 6 months ago
Partitioned Linear Programming Approximations for MDPs
Approximate linear programming (ALP) is an efficient approach to solving large factored Markov decision processes (MDPs). The main idea of the method is to approximate the optimal...
Branislav Kveton, Milos Hauskrecht
EOR
2008
103views more  EOR 2008»
13 years 4 months ago
New complexity analysis of IIPMs for linear optimization based on a specific self-regular function
Primal-dual Interior-Point Methods (IPMs) have shown their ability in solving large classes of optimization problems efficiently. Feasible IPMs require a strictly feasible startin...
Maziar Salahi, M. Reza Peyghami, Tamás Terl...
ICASSP
2008
IEEE
13 years 11 months ago
Blind separation of non-negative sources by convex analysis: Effective method using linear programming
We recently reported a criterion for blind separation of non-negative sources, using a new concept called convex analysis for mixtures of non-negative sources (CAMNS). Under some ...
Tsung-Han Chan, Wing-Kin Ma, Chong-Yung Chi, Yue W...
JMLR
2010
102views more  JMLR 2010»
12 years 11 months ago
Efficient Algorithms for Conditional Independence Inference
The topic of the paper is computer testing of (probabilistic) conditional independence (CI) implications by an algebraic method of structural imsets. The basic idea is to transfor...
Remco R. Bouckaert, Raymond Hemmecke, Silvia Lindn...
SIAMJO
2002
122views more  SIAMJO 2002»
13 years 4 months ago
Robust Filtering via Semidefinite Programming with Applications to Target Tracking
In this paper we propose a novel finite-horizon, discrete-time, time-varying filtering method based on the robust semidefinite programming (SDP) technique. The proposed method prov...
Lingjie Li, Zhi-Quan Luo, Timothy N. Davidson, Kon...