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115
Voted
UAI
1998
14 years 11 months ago
1998
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
85
Voted
UAI
1997
14 years 11 months ago
1997
Much recent research in decision theoretic planning has adopted Markov decision processes (MDPs) as the model of choice, and has attempted to make their solution more tractable by...
108
Voted
UAI
2008
14 years 11 months ago
2008
In this work we present Cutting Plane Inference (CPI), a Maximum A Posteriori (MAP) inference method for Statistical Relational Learning. Framed in terms of Markov Logic and inspi...
105
Voted
UAI
2008
14 years 11 months ago
2008
In this paper we introduce Refractor Importance Sampling (RIS), an improvement to reduce error variance in Bayesian network importance sampling propagation under evidential reason...
88
Voted
UAI
2008
14 years 11 months ago
2008
Bounded policy iteration is an approach to solving infinitehorizon POMDPs that represents policies as stochastic finitestate controllers and iteratively improves a controller by a...