5785 search results - page 59 / 1157 » Approximability of Probability Distributions |
104
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NIPS
2003
15 years 2 months ago
2003
In models that define probabilities via energies, maximum likelihood learning typically involves using Markov Chain Monte Carlo to sample from the model’s distribution. If the ...
129
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PKDD
2010
Springer
14 years 12 months ago
2010
Springer
In this paper we propose a Bayesian model for multi-task feature selection. This model is based on a generalized spike and slab sparse prior distribution that enforces the selectio...
118
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ISIPTA
2005
IEEE
15 years 7 months ago
2005
IEEE
When considering sampling models described by a distribution from an exponential family, it is possible to create two types of imprecise probability models. One is based on the co...
GLOBECOM
2009
IEEE
15 years 8 months ago
2009
IEEE
—Current 802.11 networks do not typically achieve the maximum potential throughput despite link adaptation and crosslayer optimization techniques designed to alleviate many cause...
108
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ICCAD
1993
IEEE
15 years 5 months ago
1993
IEEE
A new technique for design centering, and for polytope approximation of the feasible region for a design are presented. In the rst phase, the feasible region is approximated by a ...