91 search results - page 8 / 19 » Bayesian learning of joint distributions of objects |
135
Voted
CORR
2007
Springer
15 years 3 months ago
2007
Springer
Sequential change diagnosis is the joint problem of detection and identification of a sudden and unobservable change in the distribution of a random sequence. In this problem, the...
139
Voted
ICML
2009
IEEE
16 years 4 months ago
2009
IEEE
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
140
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ICML
2009
IEEE
16 years 4 months ago
2009
IEEE
This paper gives an efficient Bayesian method for inferring the parameters of a PlackettLuce ranking model. Such models are parameterised distributions over rankings of a finite s...
144
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GECCO
2004
Springer
15 years 9 months ago
2004
Springer
This paper describes a continuous estimation of distribution algorithm (EDA) to solve decomposable, real-valued optimization problems quickly, accurately, and reliably. This is the...
156
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ML
2012
ACM
13 years 11 months ago
2012
ACM
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...