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CORR
2012
Springer
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12 years 23 days ago
Learning Determinantal Point Processes
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
Alex Kulesza, Ben Taskar
UAI
2004
13 years 6 months ago
Variational Chernoff Bounds for Graphical Models
Recent research has made significant progress on the problem of bounding log partition functions for exponential family graphical models. Such bounds have associated dual paramete...
Pradeep D. Ravikumar, John D. Lafferty
ECSQARU
1995
Springer
13 years 8 months ago
Parametric Structure of Probabilities in Bayesian Networks
The paper presents a method for uncertainty propagation in Bayesian networks in symbolic, as opposed to numeric, form. The algebraic structure of probabilities is characterized. Th...
Enrique Castillo, José Manuel Gutiér...
ICANN
2007
Springer
13 years 11 months ago
Theoretical Analysis of Accuracy of Gaussian Belief Propagation
Abstract. Belief propagation (BP) is the calculation method which enables us to obtain the marginal probabilities with a tractable computational cost. BP is known to provide true m...
Yu Nishiyama, Sumio Watanabe