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CMA-ES
Results: 283

#	Item
31	Compilation of Results on the 2005 CEC Benchmark Function Set Nikolaus Hansen Computational Laboratory (CoLab) Institute of Computational Science ETH Zurich Add to Reading List Source URL: web.mysites.ntu.edu.sg Language: English - Date: 2010-12-27 21:29:50 Evolutionary algorithms CMA-ES Stochastic optimization Unimodality Function Algorithm L-function Mathematics Functions and mappings Mathematical analysis
32	Microsoft Word - Tech-Report-May-4-06.doc Add to Reading List Source URL: web.mysites.ntu.edu.sg Language: English - Date: 2010-12-27 21:29:51 Abstract algebra Linear algebra Mathematical optimization Operations research Unimodality Vector space CMA-ES Function Global optimum Mathematics Algebra Functions and mappings
33	Journal of Machine Learning Research[removed] Submitted 10/07; Revised 3/08; Published 6/08 Shark Christian Igel Add to Reading List Source URL: www.jmlr.org Language: English - Date: 2008-06-16 14:58:30 Neural networks Applied mathematics Evolutionary algorithms Stochastic optimization Mathematical optimization Support vector machine CMA-ES Genetic algorithm Artificial neural network Machine learning Cybernetics Statistics
34	CrossMark_Color_Stacked_p Add to Reading List Source URL: code.ulb.ac.be Language: English - Date: 2014-10-21 12:04:14 Stochastic optimization Operations research Ant colony optimization algorithms Evolutionary algorithms Mathematical optimization Algorithm CMA-ES Optimization problem Travelling salesman problem Applied mathematics Theoretical computer science Mathematics
35	Toward PAC-Learning of Weights from Qualitative Distance Information Add to Reading List Source URL: aaai.org Language: English - Date: 2006-01-11 08:20:13 Neural networks Group theory Linear algebra Vector space Probably approximately correct learning Logarithm Information bottleneck method CMA-ES Algebra Mathematics Multivariate statistics
36	Microsoft Word - ICOSSAR2013_Papadimitriou.doc Add to Reading List Source URL: www.cse-lab.ethz.ch Language: English - Date: 2013-11-12 04:25:13 Design of experiments Numerical analysis Surrogate model Kriging Markov chain Monte Carlo Bayesian inference Normal distribution CMA-ES Mathematical optimization Statistics Bayesian statistics Statistical theory
37	EVOLUTIONARY AND DETERMINISTIC METHODS FOR DESIGN, OPTIMIZATION AND CONTROL C. Poloni, D. Quagliarella, J. P´ eriaux, N. Gauger and K. Giannakoglou (Eds.) c CIRA, Capua, Italy 2011 Add to Reading List Source URL: www.cse-lab.ethz.ch Language: English - Date: 2012-11-15 12:28:22 Stochastic optimization Applied mathematics Evolution Program optimization Mathematical optimization Fitness landscape CMA-ES Swarm behaviour Nature Biology Evolutionary algorithms Cybernetics
38	Adapting Weighted Aggregation for Multiobjective Evolution Strategies Yaochu Jin, Tatsuya Okabe, and Bernhard Sendhoff Future Technology Research Honda R&D Europe (D) GmbH[removed]Offenbach/Main, Germany Add to Reading List Source URL: epubs.surrey.ac.uk Language: English - Date: 2013-09-23 15:27:45 Numerical analysis Multi-objective optimization Pareto efficiency Variance CMA-ES Genetic algorithm Algorithm Mathematical optimization Applied mathematics Mathematics
39	Multi-Dimensional Deep Memory Go-Player for Parameter Exploring Policy Gradients Mandy Gr¨ uttner1 , Frank Sehnke1 , Tom Schaul2 , and J¨ urgen Schmidhuber2,3 1 Add to Reading List Source URL: www6.in.tum.de Language: English - Date: 2013-05-15 08:23:27 Statistics Science Computational statistics Evolutionary algorithms Stochastic optimization Artificial neural network Recurrent neural network Dimensional analysis CMA-ES Neural networks Computational neuroscience Cybernetics
40	Parametric Policy Gradients for Robotics Frank Sehnke, Thomas R¨uckstieß, Martin Felder and J¨urgen Schmidhuber Abstract— Slow convergence is a major problem for policy gradient methods. It is a consequence of the f Add to Reading List Source URL: www6.in.tum.de Language: English - Date: 2013-05-15 08:23:49 Estimation theory Dimensional analysis CMA-ES Applied mathematics Science Measurement Statistics Reinforcement learning