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» Budgeted Distribution Learning of Belief Net Parameters
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CIDM
2009
IEEE
14 years 1 days ago
A new hybrid method for Bayesian network learning With dependency constraints
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...
Oliver Schulte, Gustavo Frigo, Russell Greiner, We...
FTDCS
1999
IEEE
13 years 9 months ago
Lessons Learned from Building a Web-Based Spatial Data Discovery Facility
This paper discusses the lessons learned and decisions made while designing and developing a web-based application for the National Spatial Information Framework (NSIF) of South A...
Ferdie Danzfuss, Judith Bishop
AMAI
2008
Springer
13 years 5 months ago
Bayesian learning of Bayesian networks with informative priors
This paper presents and evaluates an approach to Bayesian model averaging where the models are Bayesian nets (BNs). Prior distributions are defined using stochastic logic programs...
Nicos Angelopoulos, James Cussens
CORR
2012
Springer
170views Education» more  CORR 2012»
12 years 1 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson
RSS
2007
176views Robotics» more  RSS 2007»
13 years 6 months ago
Active Policy Learning for Robot Planning and Exploration under Uncertainty
Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...