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IAT
2005
IEEE
15 years 3 months ago
Decomposing Large-Scale POMDP Via Belief State Analysis
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
Xin Li, William K. Cheung, Jiming Liu
CIMAGING
2010
195views Hardware» more  CIMAGING 2010»
14 years 11 months ago
SPIRAL out of convexity: sparsity-regularized algorithms for photon-limited imaging
The observations in many applications consist of counts of discrete events, such as photons hitting a detector, which cannot be effectively modeled using an additive bounded or Ga...
Zachary T. Harmany, Roummel F. Marcia, Rebecca Wil...
JMLR
2006
92views more  JMLR 2006»
14 years 9 months ago
Linear Programs for Hypotheses Selection in Probabilistic Inference Models
We consider an optimization problem in probabilistic inference: Given n hypotheses Hj, m possible observations Ok, their conditional probabilities pk j, and a particular Ok, selec...
Anders Bergkvist, Peter Damaschke, Marcel Lüt...
TCS
2010
14 years 8 months ago
Active learning in heteroscedastic noise
We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...
András Antos, Varun Grover, Csaba Szepesv&a...
IPPS
1999
IEEE
15 years 2 months ago
COWL: Copy-On-Write for Logic Programs
In order for parallel logic programming systems to become popular, they should serve the broadest range of applications. To achieve this goal, designers of parallel logic programm...
Vítor Santos Costa