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» Approximate Expectation Maximization
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ATAL
2008
Springer
15 years 5 months ago
Sigma point policy iteration
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...
116
Voted
DIALM
2008
ACM
135views Algorithms» more  DIALM 2008»
15 years 5 months ago
Symmetric range assignment with disjoint MST constraints
If V is a set of n points in the unit square [0, 1]2 , and if R : V + is an assignment of positive real numbers (radii) to to those points, define a graph G(R) as follows: {v, w}...
Eric Schmutz
123
Voted
ECAI
2010
Springer
15 years 4 months ago
EP for Efficient Stochastic Control with Obstacles
Abstract. We address the problem of continuous stochastic optimal control in the presence of hard obstacles. Due to the non-smooth character of the obstacles, the traditional appro...
Thomas Mensink, Jakob J. Verbeek, Bert Kappen
136
Voted
CORR
2010
Springer
67views Education» more  CORR 2010»
15 years 3 months ago
Similarity-based Reasoning in Qualified Logic Programming
Similarity-based Logic Programming (briefly, SLP) has been proposed to enhance the LP paradigm with a kind of approximate reasoning which supports flexible information retrieval a...
Rafael Caballero, Mario Rodríguez-Artalejo,...
119
Voted
CORR
2006
Springer
123views Education» more  CORR 2006»
15 years 3 months ago
Counting good truth assignments of random k-SAT formulae
We present a deterministic approximation algorithm to compute logarithm of the number of `good' truth assignments for a random k-satisfiability (k-SAT) formula in polynomial ...
Andrea Montanari, Devavrat Shah