probabilistic-optimization.org probabilistic-optimization.org

probabilistic-optimization.org

Probabilistic-Optimization.org

Information efficient search and optimization. This site collects and presents results from an ongoing research effort to construct optimization algorithms from a probabilistic basis. Extremum of a complicated, unknown function; but just finding one. Local minimum of a relatively simple but very high-dimensional function can also be a formidable challenge. Probabilistic optimization algorithms can . Make efficient use of information. Both by choosing evaluation points efficiently, and by making efficient...

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Probabilistic-Optimization.org | probabilistic-optimization.org Reviews
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Information efficient search and optimization. This site collects and presents results from an ongoing research effort to construct optimization algorithms from a probabilistic basis. Extremum of a complicated, unknown function; but just finding one. Local minimum of a relatively simple but very high-dimensional function can also be a formidable challenge. Probabilistic optimization algorithms can . Make efficient use of information. Both by choosing evaluation points efficiently, and by making efficient...
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1 probabilistic optimization
2 algorithms and publications
3 quasi newton methods
4 stochastic optimization
5 global optimization
6 people
7 philipp hennig
8 christian schuler
9 martin kiefel
10 optimization
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Probabilistic-Optimization.org | probabilistic-optimization.org Reviews

https://probabilistic-optimization.org

Information efficient search and optimization. This site collects and presents results from an ongoing research effort to construct optimization algorithms from a probabilistic basis. Extremum of a complicated, unknown function; but just finding one. Local minimum of a relatively simple but very high-dimensional function can also be a formidable challenge. Probabilistic optimization algorithms can . Make efficient use of information. Both by choosing evaluation points efficiently, and by making efficient...

INTERNAL PAGES

probabilistic-optimization.org probabilistic-optimization.org
1

Probabilistic-Optimization.org

http://www.probabilistic-optimization.org/index.html

Information efficient search and optimization. This site collects and presents results from an ongoing research effort to construct optimization algorithms from a probabilistic basis. Extremum of a complicated, unknown function; but just finding one. Local minimum of a relatively simple but very high-dimensional function can also be a formidable challenge. Probabilistic optimization algorithms can . Make efficient use of information. Both by choosing evaluation points efficiently, and by making efficient...

2

Probabilistic-Optimization.org

http://www.probabilistic-optimization.org/Global.html

Information efficient search and optimization. Entropy-Search: Information-Efficient Global Optimization. Hennig, P. and Schuler, C.: Entropy Search for Information-Efficient Global Optimization. Journal of Machine Learning Research (JMLR) Vol. 13, 2012, in press. Please cite when you use this algorithm. After download, refer to the README.txt file.

3

Probabilistic-Optimization.org

http://www.probabilistic-optimization.org/Newton.html

Information efficient search and optimization. HKopt: Nonparametric Bayesian Quasi-Newton Optimization. Hennig, P. & Kiefel, M.: Quasi-Newton methods: a new direction. Proceedings of the 29th International Conference on Machine Learning (ICML), Edinburgh, June 2012 (Please cite this work when you use this algorithm). After download, refer to the README.txt file. HK opt 1.0.zip. Implementation by Carl Rasmussen. Details on the code can be found in an accompanying readme.txt. Tech Report, Argonne National ...

4

Probabilistic-Optimization.org

http://www.probabilistic-optimization.org/NoisyNewton.html

Information efficient search and optimization. Quasi-Newton Methods for Noisy Objectives. Hennig, P.: Fast probabilistic optimization from noisy gradients. Proceedings of the 30th International Conference on Machine Learning (ICML); Atlanta, Georgia; June 2013 (Please cite this work when you use this algorithm). After download, refer to the README.txt file. NoisyNewton v0.1.zip. As we showed in our work quasi-Newton methods. Ideally with a simple reduction case.

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