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JMLR
2010
139views more  JMLR 2010»
13 years 4 months ago
Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines
Alternating Gibbs sampling is the most common scheme used for sampling from Restricted Boltzmann Machines (RBM), a crucial component in deep architectures such as Deep Belief Netw...
Guillaume Desjardins, Aaron C. Courville, Yoshua B...
DSN
2006
IEEE
14 years 4 months ago
Automatic Recovery Using Bounded Partially Observable Markov Decision Processes
This paper provides a technique, based on partially observable Markov decision processes (POMDPs), for building automatic recovery controllers to guide distributed system recovery...
Kaustubh R. Joshi, William H. Sanders, Matti A. Hi...
IJCNN
2000
IEEE
14 years 1 months ago
Competing Hidden Markov Models on the Self-Organizing Map
This paper presents an unsupervised segmentation method for feature sequences based on competitivelearning hidden Markov models. Models associated with the nodes of the Self-Organ...
Panu Somervuo
FLAIRS
2001
13 years 11 months ago
A Practical Markov Chain Monte Carlo Approach to Decision Problems
Decisionand optimizationproblemsinvolvinggraphsarise in manyareas of artificial intelligence, including probabilistic networks, robot navigation, and network design. Manysuch prob...
Timothy Huang, Yuriy Nevmyvaka
MONET
2007
98views more  MONET 2007»
13 years 9 months ago
A Markov Model for Indoor Ultra-wideband Channel with People Shadowing
Abstract For an indoor ultra-wideband (UWB) communication system, the line-of-sight (LOS) between the transmitter and receiver may be frequently blocked by moving people. Blocking ...
Ruonan Zhang, Lin Cai