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» Solving Hierarchical Optimization Problems Using MOEAs
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MP
2006
123views more  MP 2006»
15 years 3 months ago
New interval methods for constrained global optimization
Abstract. Interval analysis is a powerful tool which allows to design branch-and-bound algorithms able to solve many global optimization problems. In this paper we present new adap...
Mihály Csaba Markót, J. Ferná...
113
Voted
ECAI
2006
Springer
15 years 7 months ago
Random Subset Optimization
Some of the most successful algorithms for satisfiability, such as Walksat, are based on random walks. Similarly, local search algorithms for solving constraint optimization proble...
Boi Faltings, Quang Huy Nguyen
WCE
2007
15 years 4 months ago
Neural Networks for Optimal Control of Aircraft Landing Systems
Abstract—In this work we present a variational formulation for a multilayer perceptron neural network. With this formulation any learning task for the neural network is defined ...
Kevin Lau, Roberto Lopez, Eugenio Oñate
135
Voted
SDM
2007
SIAM
167views Data Mining» more  SDM 2007»
15 years 5 months ago
Bandits for Taxonomies: A Model-based Approach
We consider a novel problem of learning an optimal matching, in an online fashion, between two feature spaces that are organized as taxonomies. We formulate this as a multi-armed ...
Sandeep Pandey, Deepak Agarwal, Deepayan Chakrabar...
135
Voted
AAAI
2012
13 years 6 months ago
Lagrangian Relaxation Techniques for Scalable Spatial Conservation Planning
We address the problem of spatial conservation planning in which the goal is to maximize the expected spread of cascades of an endangered species by strategically purchasing land ...
Akshat Kumar, XiaoJian Wu, Shlomo Zilberstein