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WINET
2002
80views more  WINET 2002»
15 years 6 months ago
A Homogeneous PCS network with Markov Call Arrival Process and Phase Type Cell Residence Time
In this paper, the arrival of calls (i.e., new and handoff calls) in a personal communications services (PCS) network is modeled by a Markov arrival process (MAP) in which we allow...
Attahiru Sule Alfa, Wei Li
ICASSP
2010
IEEE
15 years 5 months ago
Learning in Gaussian Markov random fields
This paper addresses the problem of state estimation in the case where the prior distribution of the states is not perfectly known but instead is parameterized by some unknown par...
Thomas J. Riedl, Andrew C. Singer, Jun Won Choi
JMLR
2010
139views more  JMLR 2010»
15 years 1 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...
CVPR
1998
IEEE
16 years 8 months ago
Markov Random Fields with Efficient Approximations
Markov Random Fields (MRF's) can be used for a wide variety of vision problems. In this paper we focus on MRF's with two-valued clique potentials, which form a generaliz...
Yuri Boykov, Olga Veksler, Ramin Zabih
MICCAI
2007
Springer
16 years 7 months ago
Object Localization Based on Markov Random Fields and Symmetry Interest Points
We present an approach to detect anatomical structures by configurations of interest points, from a single example image. The representation of the configuration is based on Markov...
Branislav Micusík, Georg Langs, Horst Bisch...