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» Approximation Algorithms for Min-Max Generalization Problems
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NIPS
1998
13 years 10 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore
CDC
2010
IEEE
151views Control Systems» more  CDC 2010»
13 years 3 months ago
On the optimal solutions of the infinite-horizon linear sensor scheduling problem
This paper studies the infinite-horizon sensor scheduling problem for linear Gaussian processes with linear measurement functions. Several important properties of the optimal infin...
Wei Zhang, Michael P. Vitus, Jianghai Hu, Alessand...
KDD
2009
ACM
173views Data Mining» more  KDD 2009»
14 years 9 months ago
Constant-factor approximation algorithms for identifying dynamic communities
We propose two approximation algorithms for identifying communities in dynamic social networks. Communities are intuitively characterized as "unusually densely knit" sub...
Chayant Tantipathananandh, Tanya Y. Berger-Wolf
FOGA
2011
13 years 6 days ago
Approximating the distribution of fitness over hamming regions
The distribution of fitness values across a set of states sharply influences the dynamics of evolutionary processes and heuristic search in combinatorial optimization. In this p...
Andrew M. Sutton, Darrell Whitley, Adele E. Howe
ATAL
2007
Springer
14 years 2 months ago
Constraint satisfaction algorithms for graphical games
We formulate the problem of computing equilibria in multiplayer games represented by arbitrary undirected graphs as a constraint satisfaction problem and present two algorithms. T...
Vishal Soni, Satinder P. Singh, Michael P. Wellman