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» Parameterized approximation of dominating set problems
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ATAL
2005
Springer
14 years 1 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
14 years 1 months ago
Convergence of stochastic search algorithms to gap-free pareto front approximations
Recently, a convergence proof of stochastic search algorithms toward finite size Pareto set approximations of continuous multi-objective optimization problems has been given. The...
Oliver Schütze, Marco Laumanns, Emilia Tantar...
CDC
2009
IEEE
147views Control Systems» more  CDC 2009»
14 years 8 days ago
A simulation-based method for aggregating Markov chains
— This paper addresses model reduction for a Markov chain on a large state space. A simulation-based framework is introduced to perform state aggregation of the Markov chain base...
Kun Deng, Prashant G. Mehta, Sean P. Meyn
STOC
2010
ACM
269views Algorithms» more  STOC 2010»
13 years 11 months ago
Approximations for the Isoperimetric and Spectral Profile of Graphs and Related Parameters
The spectral profile of a graph is a natural generalization of the classical notion of its Rayleigh quotient. Roughly speaking, given a graph G, for each 0 < < 1, the spect...
Prasad Raghavendra, David Steurer and Prasad Tetal...
SIAMCOMP
2000
104views more  SIAMCOMP 2000»
13 years 7 months ago
On the Difficulty of Designing Good Classifiers
We consider the problem of designing a near-optimal linear decision tree to classify two given point sets B and W in n. A linear decision tree de nes a polyhedral subdivision of sp...
Michelangelo Grigni, Vincent Mirelli, Christos H. ...