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AAAI
2012
13 years 5 days ago
Kernel-Based Reinforcement Learning on Representative States
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
Branislav Kveton, Georgios Theocharous
CONSTRAINTS
2000
96views more  CONSTRAINTS 2000»
14 years 9 months ago
A Comparison of Traditional and Constraint-based Heuristic Methods on Vehicle Routing Problems with Side Constraints
The vehicle routing problem (VRP) is a variant of the familiar travelling salesperson problem (TSP). In the VRP we are to perform a number of visits, using a number of vehicles of ...
Philip Kilby, Patrick Prosser, Paul Shaw
FOCS
1997
IEEE
15 years 2 months ago
The Computational Complexity of Knot and Link Problems
We consider the problem of deciding whether a polygonal knot in 3dimensional Euclidean space is unknotted, capable of being continuously deformed without self-intersection so that...
Joel Hass, J. C. Lagarias, Nicholas Pippenger
ICC
2008
IEEE
121views Communications» more  ICC 2008»
15 years 4 months ago
Maximization of Network Survival Time in the Event of Intelligent and Malicious Attacks
—It is not possible to ensure that a network is absolutely secure. Therefore, network operators must continually change their defense strategies to counter attackers who constant...
Po-Hao Tsang, Frank Yeong-Sung Lin, Chun-Wei Chen
SODA
2012
ACM
217views Algorithms» more  SODA 2012»
13 years 7 days ago
Deterministic construction of an approximate M-ellipsoid and its applications to derandomizing lattice algorithms
We give a deterministic O(log n)n -time and space algorithm for the Shortest Vector Problem (SVP) of a lattice under any norm, improving on the previous best deterministic nO(n) -...
Daniel Dadush, Santosh Vempala