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CDC
2009
IEEE
117views Control Systems» more  CDC 2009»
15 years 8 months ago
Risk sensitive robust support vector machines
— We propose a new family of classification algorithms in the spirit of support vector machines, that builds in non-conservative protection to noise and controls overfitting. O...
Huan Xu, Constantine Caramanis, Shie Mannor, Sungh...
FLAIRS
2004
15 years 5 months ago
Developing Task Specific Sensing Strategies Using Reinforcement Learning
Robots that can adapt and perform multiple tasks promise to be a powerful tool with many applications. In order to achieve such robots, control systems have to be constructed that...
Srividhya Rajendran, Manfred Huber
129
Voted
AAAI
1997
15 years 5 months ago
Incremental Methods for Computing Bounds in Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...
Milos Hauskrecht
140
Voted
GECCO
2010
Springer
248views Optimization» more  GECCO 2010»
15 years 7 months ago
Integrating decision space diversity into hypervolume-based multiobjective search
Multiobjective optimization in general aims at learning about the problem at hand. Usually the focus lies on objective space properties such as the front shape and the distributio...
Tamara Ulrich, Johannes Bader, Eckart Zitzler
131
Voted
IPPS
1997
IEEE
15 years 8 months ago
Control Schemes in a Generalized Utility for Parallel Branch-and-Bound Algorithms
Branch-and-bound algorithms are general methods applicable to various combinatorial optimization problems and parallelization is one of the most hopeful methods to improve these a...
Yuji Shinano, Kenichi Harada, Ryuichi Hirabayashi