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84
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UAI
2003
14 years 11 months ago
Approximate Decomposition: A Method for Bounding and Estimating Probabilistic and Deterministic Queries
In this paper, we introduce a method for approximating the solution to inference and optimization tasks in uncertain and deterministic reasoning. Such tasks are in general intract...
David Larkin
93
Voted
UAI
2003
14 years 11 months ago
Learning Riemannian Metrics
We consider the problem of learning a Riemannian metric associated with a given differentiable manifold and a set of points. Our approach to the problem involves choosing a metric...
Guy Lebanon
85
Voted
UAI
2003
14 years 11 months ago
On Local Optima in Learning Bayesian Networks
This paper proposes and evaluates the k-greedy equivalence search algorithm (KES) for learning Bayesian networks (BNs) from complete data. The main characteristic of KES is that i...
Jens D. Nielsen, Tomás Kocka, José M...
103
Voted
UAI
2003
14 years 11 months ago
Optimal Limited Contingency Planning
For a given problem, the optimal Markov policy over a finite horizon is a conditional plan containing a potentially large number of branches. However, there are applications wher...
Nicolas Meuleau, David E. Smith
76
Voted
UAI
2003
14 years 11 months ago
Decentralized Sensor Fusion with Distributed Particle Filters
This paper presents a scalable Bayesian technique for decentralized state estimation from multiple platforms in dynamic environments. As has long been recognized, centralized arch...
Matthew Rosencrantz, Geoffrey J. Gordon, Sebastian...