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UAI
1998
13 years 9 months ago
Flexible Decomposition Algorithms for Weakly Coupled Markov Decision Problems
This paper presents two new approaches to decomposing and solving large Markov decision problems (MDPs), a partial decoupling method and a complete decoupling method. In these app...
Ronald Parr
IPPS
2005
IEEE
14 years 1 months ago
A Powerful Direct Mechanism for Optimal WWW Content Replication
This paper addresses the problem of fine-grained data replication in large distributed systems, such as the Internet, so as to minimize the user access delays. With fine-grained d...
Samee Ullah Khan, Ishfaq Ahmad
AAAI
1997
13 years 9 months ago
Incremental Methods for Computing Bounds in Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...
Milos Hauskrecht
AAAI
1998
13 years 9 months ago
A* with Bounded Costs
A key assumption of all problem-solving approaches based on utility theory, including heuristic search, is that we can assign a utility or cost to each state. This in turn require...
Brian Logan, Natasha Alechina
FOCS
2005
IEEE
14 years 1 months ago
On Learning Mixtures of Heavy-Tailed Distributions
We consider the problem of learning mixtures of arbitrary symmetric distributions. We formulate sufficient separation conditions and present a learning algorithm with provable gua...
Anirban Dasgupta, John E. Hopcroft, Jon M. Kleinbe...