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ANOR
2004
79views more  ANOR 2004»
15 years 3 months ago
Preference-Based Search and Multi-Criteria Optimization
Many real-world AI problems (e.g. in configuration) are weakly constrained, thus requiring a mechanism for characterizing and finding the preferred solutions. Preferencebased sear...
Ulrich Junker
147
Voted
JMLR
2008
209views more  JMLR 2008»
15 years 3 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
TOG
2008
101views more  TOG 2008»
15 years 3 months ago
Synthesis of constrained walking skills
Simulated characters in simulated worlds require simulated skills. We develop control strategies that enable physically-simulated characters to dynamically navigate environments w...
Stelian Coros, Philippe Beaudoin, KangKang Yin, Mi...
133
Voted
GECCO
2007
Springer
209views Optimization» more  GECCO 2007»
15 years 9 months ago
Guided hyperplane evolutionary algorithm
A new evolutionary technique for multicriteria optimization called Guiding Hyper-plane Evolutionary Algorithm (GHEA) is proposed. The originality of the approach consists in the f...
Corina Rotar, D. Dumitrescu, Rodica Ioana Lung
EC
2012
289views ECommerce» more  EC 2012»
13 years 11 months ago
Multimodal Optimization Using a Bi-Objective Evolutionary Algorithm
In a multimodal optimization task, the main purpose is to find multiple optimal solutions (global and local), so that the user can have a better knowledge about different optima...
Kalyanmoy Deb, Amit Saha