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AAAI
2012
13 years 6 months 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»
15 years 3 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
108
Voted
FOCS
1997
IEEE
15 years 8 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 10 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
142
Voted
SODA
2012
ACM
217views Algorithms» more  SODA 2012»
13 years 6 months 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