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ORCIDAnne Auger
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- affiliation: INRIA, France
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2020 – today
- 2024
[j22]Armand Gissler
, Anne Auger, Nikolaus Hansen:
Asymptotic estimations of a perturbed symmetric eigenproblem. Appl. Math. Lett. 150: 108951 (2024)- [c91]Tristan Marty, Nikolaus Hansen, Anne Auger, Yann Semet, Sébastien Héron:
LB+IC-CMA-ES: Two Simple Modifications of CMA-ES to Handle Mixed-Integer Problems. PPSN (2) 2024: 284-299 - [i28]Armand Gissler, Anne Auger, Nikolaus Hansen:
Asymptotic estimations of a perturbed symmetric eigenproblem. CoRR abs/2403.06983 (2024) - 2023
- [j21]Cheikh Toure, Anne Auger, Nikolaus Hansen:
Global linear convergence of evolution strategies with recombination on scaling-invariant functions. J. Glob. Optim. 86(1): 163-203 (2023) - [c90]Anne Auger, Nikolaus Hansen:
An Introduction to Scientific Experimentation and Benchmarking. GECCO Companion 2023: 854-877 - [c89]Tristan Marty, Yann Semet, Anne Auger, Sébastien Héron, Nikolaus Hansen:
Benchmarking CMA-ES with Basic Integer Handling on a Mixed-Integer Test Problem Suite. GECCO Companion 2023: 1628-1635 - [i27]Anne Auger, Peter A. N. Bosman, Pascal Kerschke, Darrell Whitley, Lennart Schäpermeier:
Challenges in Benchmarking Optimization Heuristics (Dagstuhl Seminar 23251). Dagstuhl Reports 13(6): 55-80 (2023) - 2022
- [j20]Dimo Brockhoff, Anne Auger, Nikolaus Hansen, Tea Tusar:
Using Well-Understood Single-Objective Functions in Multiobjective Black-Box Optimization Test Suites. Evol. Comput. 30(2): 165-193 (2022) - [j19]Youhei Akimoto, Anne Auger, Tobias Glasmachers, Daiki Morinaga:
Global Linear Convergence of Evolution Strategies on More than Smooth Strongly Convex Functions. SIAM J. Optim. 32(2): 1402-1429 (2022) - [j18]Nikolaus Hansen, Anne Auger, Dimo Brockhoff, Tea Tusar:
Anytime Performance Assessment in Blackbox Optimization Benchmarking. IEEE Trans. Evol. Comput. 26(6): 1293-1305 (2022) - [c88]Armand Gissler, Anne Auger, Nikolaus Hansen:
Learning rate adaptation by line search in evolution strategies with recombination. GECCO 2022: 630-638 - [c87]Anne Auger, Nikolaus Hansen:
A (biased) introduction to benchmarking. GECCO Companion 2022: 801-823 - [i26]Anne Auger, Carlos M. Fonseca, Tobias Friedrich, Johannes Lengler:
Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 22081). Dagstuhl Reports 12(2): 87-102 (2022) - 2021
- [j17]Anne Auger, Per Kristian Lehre:
Preface to the Special Issue on Theory of Genetic and Evolutionary Computation. Algorithmica 83(4): 903-905 (2021) - [j16]Cheikh Toure, Armand Gissler, Anne Auger, Nikolaus Hansen:
Scaling-invariant Functions versus Positively Homogeneous Functions. J. Optim. Theory Appl. 191(1): 363-383 (2021) - [j15]Nikolaus Hansen, Anne Auger, Raymond Ros, Olaf Mersmann, Tea Tusar, Dimo Brockhoff:
COCO: a platform for comparing continuous optimizers in a black-box setting. Optim. Methods Softw. 36(1): 114-144 (2021) - [c86]Anne Auger, Nikolaus Hansen:
Benchmarking: state-of-the-art and beyond. GECCO Companion 2021: 339-340 - [c85]Dimo Brockhoff, Baptiste Plaquevent-Jourdain, Anne Auger, Nikolaus Hansen:
DMS and MultiGLODS: black-box optimization benchmarking of two direct search methods on the bbob-biobj test suite. GECCO Companion 2021: 1251-1258 - 2020
- [j14]Konstantinos Varelas, Ouassim Ait ElHara, Dimo Brockhoff, Nikolaus Hansen, Duc Manh Nguyen, Tea Tusar, Anne Auger:
Benchmarking large-scale continuous optimizers: The bbob-largescale testbed, a COCO software guide and beyond. Appl. Soft Comput. 97(Part): 106737 (2020) - [j13]Youhei Akimoto, Anne Auger, Nikolaus Hansen:
Quality gain analysis of the weighted recombination evolution strategy on general convex quadratic functions. Theor. Comput. Sci. 832: 42-67 (2020) - [j12]Asma Atamna, Anne Auger, Nikolaus Hansen:
On invariance and linear convergence of evolution strategies with augmented Lagrangian constraint handling. Theor. Comput. Sci. 832: 68-97 (2020) - [j11]Pietro S. Oliveto, Anne Auger, Francisco Chicano, Carlos M. Fonseca:
Guest Editorial Special Issue on Theoretical Foundations of Evolutionary Computation. IEEE Trans. Evol. Comput. 24(6): 993-994 (2020) - [c84]Konstantinos Varelas, Anne Auger, Nikolaus Hansen:
Sparse Inverse Covariance Learning for CMA-ES with Graphical Lasso. PPSN (1) 2020: 707-718 - [i25]Youhei Akimoto, Anne Auger, Tobias Glasmachers, Daiki Morinaga:
Global Linear Convergence of Evolution Strategies on More Than Smooth Strongly Convex Functions. CoRR abs/2009.08647 (2020)
2010 – 2019
- 2019
- [c83]Cheikh Toure, Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
On Bi-objective Convex-Quadratic Problems. EMO 2019: 3-14 - [c82]Cheikh Touré, Nikolaus Hansen, Anne Auger, Dimo Brockhoff:
Uncrowded hypervolume improvement: COMO-CMA-ES and the sofomore framework. GECCO 2019: 638-646 - [e7]Anne Auger, Thomas Stützle:
Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2019, Prague, Czech Republic, July 13-17, 2019. ACM 2019, ISBN 978-1-4503-6111-8 [contents] - [e6]Manuel López-Ibáñez, Anne Auger, Thomas Stützle:
Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2019, Prague, Czech Republic, July 13-17, 2019. ACM 2019, ISBN 978-1-4503-6748-6 [contents] - [i24]Ouassim Ait ElHara, Konstantinos Varelas, Duc Manh Nguyen, Tea Tusar, Dimo Brockhoff, Nikolaus Hansen, Anne Auger:
COCO: The Large Scale Black-Box Optimization Benchmarking (bbob-largescale) Test Suite. CoRR abs/1903.06396 (2019) - [i23]Cheikh Touré, Nikolaus Hansen, Anne Auger, Dimo Brockhoff:
Uncrowded Hypervolume Improvement: COMO-CMA-ES and the Sofomore framework. CoRR abs/1904.08823 (2019) - 2018
- [c81]Youhei Akimoto, Anne Auger, Tobias Glasmachers:
Drift theory in continuous search spaces: expected hitting time of the (1 + 1)-ES with 1/5 success rule. GECCO 2018: 801-808 - [c80]Aurore Blelly, Matheus Felipe-Gomes, Anne Auger, Dimo Brockhoff:
Stopping criteria, initialization, and implementations of BFGS and their effect on the BBOB test suite. GECCO (Companion) 2018: 1513-1517 - [c79]Konstantinos Varelas, Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Ouassim Ait ElHara, Yann Semet, Rami Kassab, Frédéric Barbaresco:
A Comparative Study of Large-Scale Variants of CMA-ES. PPSN (1) 2018: 3-15 - [e5]Anne Auger, Carlos M. Fonseca, Nuno Lourenço, Penousal Machado, Luís Paquete, L. Darrell Whitley:
Parallel Problem Solving from Nature - PPSN XV - 15th International Conference, Coimbra, Portugal, September 8-12, 2018, Proceedings, Part I. Lecture Notes in Computer Science 11101, Springer 2018, ISBN 978-3-319-99252-5 [contents] - [e4]Anne Auger, Carlos M. Fonseca, Nuno Lourenço, Penousal Machado, Luís Paquete, L. Darrell Whitley:
Parallel Problem Solving from Nature - PPSN XV - 15th International Conference, Coimbra, Portugal, September 8-12, 2018, Proceedings, Part II. Lecture Notes in Computer Science 11102, Springer 2018, ISBN 978-3-319-99258-7 [contents] - [i22]Youhei Akimoto, Anne Auger, Tobias Glasmachers:
Drift Theory in Continuous Search Spaces: Expected Hitting Time of the (1+1)-ES with 1/5 Success Rule. CoRR abs/1802.03209 (2018) - [i21]Cheikh Toure, Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
On Bi-Objective convex-quadratic problems. CoRR abs/1812.00289 (2018) - [i20]Eric Benhamou, Jamal Atif, Rida Laraki, Anne Auger:
A new approach to learning in Dynamic Bayesian Networks (DBNs). CoRR abs/1812.09027 (2018) - [i19]Eric Benhamou, Jamal Atif, Rida Laraki, Anne Auger:
A discrete version of CMA-ES. CoRR abs/1812.11859 (2018) - 2017
- [j10]Yann Ollivier, Ludovic Arnold, Anne Auger, Nikolaus Hansen:
Information-Geometric Optimization Algorithms: A Unifying Picture via Invariance Principles. J. Mach. Learn. Res. 18: 18:1-18:65 (2017) - [c78]Dimo Brockhoff, Anne Auger, Nikolaus Hansen, Tea Tusar:
Quantitative Performance Assessment of Multiobjective Optimizers: The Average Runtime Attainment Function. EMO 2017: 103-119 - [c77]Youhei Akimoto, Anne Auger, Nikolaus Hansen:
Quality Gain Analysis of the Weighted Recombination Evolution Strategy on General Convex Quadratic Functions. FOGA 2017: 111-126 - [c76]Asma Atamna, Anne Auger, Nikolaus Hansen:
Linearly Convergent Evolution Strategies via Augmented Lagrangian Constraint Handling. FOGA 2017: 149-161 - [c75]Anne Auger, Nikolaus Hansen:
Introduction to randomized continuous optimization. GECCO (Companion) 2017: 319-334 - 2016
- [b2]Anne Auger:
Thèse d'habilitation à diriger des recherches "Analysis of Comparison-based Stochastic Continuous Black-Box Optimization Algorithms". (Thèse d'habilitation à diriger des recherches "Analysis of Comparison-based Stochastic Continuous Black-Box Optimization Algorithms"). University of Paris-Sud, France, 2016 - [j9]Anne Auger, Nikolaus Hansen:
Linear Convergence of Comparison-based Step-size Adaptive Randomized Search via Stability of Markov Chains. SIAM J. Optim. 26(3): 1589-1624 (2016) - [c74]Ouassim Ait ElHara, Anne Auger, Nikolaus Hansen:
Permuted Orthogonal Block-Diagonal Transformation Matrices for Large Scale Optimization Benchmarking. GECCO 2016: 189-196 - [c73]Asma Atamna, Anne Auger, Nikolaus Hansen:
Analysis of Linear Convergence of a (1 + 1)-ES with Augmented Lagrangian Constraint Handling. GECCO 2016: 213-220 - [c72]Youhei Akimoto, Anne Auger, Nikolaus Hansen:
Introduction to Randomized Continuous Optimization. GECCO (Companion) 2016: 333-355 - [c71]Youhei Akimoto, Anne Auger, Nikolaus Hansen:
CMA-ES and Advanced Adaptation Mechanisms. GECCO (Companion) 2016: 533-562 - [c70]Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tusar, Tea Tusar, Tobias Wagner:
GECCO'16 Black-Box Optimization Benchmarking Workshop (BBOB-2016): Workshop Chairs' Welcome Message. GECCO (Companion) 2016: 1167 - [c69]Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tusar, Tea Tusar, Tobias Wagner:
Benchmarking the Pure Random Search on the Bi-objective BBOB-2016 Testbed. GECCO (Companion) 2016: 1217-1223 - [c68]Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tusar, Tea Tusar, Tobias Wagner:
The Impact of Variation Operators on the Performance of SMS-EMOA on the Bi-objective BBOB-2016 Test Suite. GECCO (Companion) 2016: 1225-1232 - [c67]Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tusar, Tea Tusar, Tobias Wagner:
Benchmarking MATLAB's gamultiobj (NSGA-II) on the Bi-objective BBOB-2016 Test Suite. GECCO (Companion) 2016: 1233-1239 - [c66]Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tusar, Tea Tusar, Tobias Wagner:
Benchmarking RM-MEDA on the Bi-objective BBOB-2016 Test Suite. GECCO (Companion) 2016: 1241-1247 - [c65]Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tusar, Tea Tusar, Tobias Wagner:
The Impact of Search Volume on the Performance of RANDOMSEARCH on the Bi-objective BBOB-2016 Test Suite. GECCO (Companion) 2016: 1257-1264 - [c64]Asma Atamna, Anne Auger, Nikolaus Hansen:
Augmented Lagrangian Constraint Handling for CMA-ES - Case of a Single Linear Constraint. PPSN 2016: 181-191 - [i18]Nikolaus Hansen, Tea Tusar, Olaf Mersmann, Anne Auger, Dimo Brockhoff:
COCO: The Experimental Procedure. CoRR abs/1603.08776 (2016) - [i17]Nikolaus Hansen, Anne Auger, Olaf Mersmann, Tea Tusar, Dimo Brockhoff:
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting. CoRR abs/1603.08785 (2016) - [i16]Tea Tusar, Dimo Brockhoff, Nikolaus Hansen, Anne Auger:
COCO: The Bi-objective Black Box Optimization Benchmarking (bbob-biobj) Test Suite. CoRR abs/1604.00359 (2016) - [i15]Dimo Brockhoff, Tea Tusar, Dejan Tusar, Tobias Wagner, Nikolaus Hansen, Anne Auger:
Biobjective Performance Assessment with the COCO Platform. CoRR abs/1605.01746 (2016) - [i14]Nikolaus Hansen, Anne Auger, Dimo Brockhoff, Dejan Tusar, Tea Tusar:
COCO: Performance Assessment. CoRR abs/1605.03560 (2016) - 2015
- [j8]Alexandre Adrien Chotard, Anne Auger, Nikolaus Hansen:
Markov Chain Analysis of Cumulative Step-Size Adaptation on a Linear Constrained Problem. Evol. Comput. 23(4): 611-640 (2015) - [c63]Youhei Akimoto, Anne Auger, Nikolaus Hansen:
Continuous Optimization and CMA-ES. GECCO (Companion) 2015: 313-344 - [c62]Youhei Akimoto, Anne Auger:
Theory of Evolution Strategies and Related Algorithms. GECCO (Companion) 2015: 575-588 - [p3]Nikolaus Hansen, Dirk V. Arnold, Anne Auger:
Evolution Strategies. Handbook of Computational Intelligence 2015: 871-898 - 2014
- [c61]Alexandre Adrien Chotard, Anne Auger, Nikolaus Hansen:
Markov chain analysis of evolution strategies on a linear constraint optimization problem. IEEE Congress on Evolutionary Computation 2014: 159-166 - [c60]Youhei Akimoto, Anne Auger, Nikolaus Hansen:
Comparison-based natural gradient optimization in high dimension. GECCO 2014: 373-380 - [c59]Nikolaus Hansen, Anne Auger:
Evolution strategies and CMA-ES (covariance matrix adaptation). GECCO (Companion) 2014: 513-534 - [c58]Una-May O'Reilly, Anna Esparcia-Alcázar, Anne Auger, Carola Doerr, Anikó Ekárt, Gabriela Ochoa:
Women@GECCO 2014. GECCO (Companion) 2014: 1487-1488 - [c57]Nikolaus Hansen, Asma Atamna, Anne Auger:
How to Assess Step-Size Adaptation Mechanisms in Randomised Search. PPSN 2014: 60-69 - [p2]Nikolaus Hansen, Anne Auger:
Principled Design of Continuous Stochastic Search: From Theory to Practice. Theory and Principled Methods for the Design of Metaheuristics 2014: 145-180 - [i13]Alexandre Adrien Chotard, Anne Auger, Nikolaus Hansen:
Markov Chain Analysis of Evolution Strategies on a Linear Constraint Optimization Problem. CoRR abs/1404.3023 (2014) - 2013
- [c56]Ouassim Ait ElHara, Anne Auger, Nikolaus Hansen:
A median success rule for non-elitist evolution strategies: study of feasibility. GECCO 2013: 415-422 - [c55]Anne Auger, Nikolaus Hansen:
Tutorial CMA-ES: evolution strategies and covariance matrix adaptation. GECCO (Companion) 2013: 499-520 - [c54]Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
Benchmarking the local metamodel CMA-ES on the noiseless BBOB'2013 test bed. GECCO (Companion) 2013: 1225-1232 - [i12]Anne Auger, Nikolaus Hansen:
On Proving Linear Convergence of Comparison-based Step-size Adaptive Randomized Search on Scaling-Invariant Functions via Stability of Markov Chains. CoRR abs/1310.7697 (2013) - [i11]Anne Auger, Nikolaus Hansen:
Linear Convergence on Positively Homogeneous Functions of a Comparison Based Step-Size Adaptive Randomized Search: the (1+1) ES with Generalized One-fifth Success Rule. CoRR abs/1310.8397 (2013) - 2012
- [j7]Anne Auger, Carsten Witt:
Theory of Randomized Search Heuristics. Algorithmica 64(4): 621-622 (2012) - [j6]Anne Auger, Nikolaus Hansen, Marc Schoenauer:
Benchmarking of Continuous Black Box Optimization Algorithms. Evol. Comput. 20(4): 481 (2012) - [j5]Anne Auger, Johannes Bader, Dimo Brockhoff, Eckart Zitzler:
Hypervolume-based multiobjective optimization: Theoretical foundations and practical implications. Theor. Comput. Sci. 425: 75-103 (2012) - [c53]Dimo Brockhoff, Anne Auger, Nikolaus Hansen:
On the effect of mirroring in the IPOP active CMA-ES on the noiseless BBOB testbed. GECCO (Companion) 2012: 277-284 - [c52]Dimo Brockhoff, Anne Auger, Nikolaus Hansen:
On the impact of a small initial population size in the IPOP active CMA-ES with mirrored mutations on the noiseless BBOB testbed. GECCO (Companion) 2012: 285-290 - [c51]Dimo Brockhoff, Anne Auger, Nikolaus Hansen:
On the impact of active covariance matrix adaptation in the CMA-ES with mirrored mutations and small initial population size on the noiseless BBOB testbed. GECCO (Companion) 2012: 291-296 - [c50]Dimo Brockhoff, Anne Auger, Nikolaus Hansen:
Comparing mirrored mutations and active covariance matrix adaptation in the IPOP-CMA-ES on the noiseless BBOB testbed. GECCO (Companion) 2012: 297-304 - [c49]Anne Auger, Nikolaus Hansen:
Tutorial CMA-ES: evolution strategies and covariance matrix adaptation. GECCO (Companion) 2012: 827-848 - [c48]Youhei Akimoto, Anne Auger, Nikolaus Hansen:
Convergence of the Continuous Time Trajectories of Isotropic Evolution Strategies on Monotonic $\mathcal C^2$ -composite Functions. PPSN (1) 2012: 42-51 - [c47]Alexandre Adrien Chotard, Anne Auger, Nikolaus Hansen:
Cumulative Step-Size Adaptation on Linear Functions. PPSN (1) 2012: 72-81 - [i10]Alexandre Adrien Chotard, Anne Auger, Nikolaus Hansen:
Cumulative Step-size Adaptation on Linear Functions. CoRR abs/1206.1208 (2012) - [i9]Youhei Akimoto, Anne Auger, Nikolaus Hansen:
Convergence of the Continuous Time Trajectories of Isotropic Evolution Strategies on Monotonic C^2-composite Functions. CoRR abs/1206.4968 (2012) - [i8]Zyed Bouzarkouna, Didier Yu Ding, Anne Auger:
Well Placement Optimization under Uncertainty with CMA-ES Using the Neighborhood. CoRR abs/1209.0616 (2012) - [i7]Alexandre Adrien Chotard, Anne Auger, Nikolaus Hansen:
Cumulative Step-size Adaptation on Linear Functions. CoRR abs/1212.0139 (2012) - 2011
- [j4]Mohamed Jebalia, Anne Auger, Nikolaus Hansen:
Log-Linear Convergence and Divergence of the Scale-Invariant (1+1)-ES in Noisy Environments. Algorithmica 59(3): 425-460 (2011) - [j3]Nikolaus Hansen, Raymond Ros, Nikolas Mauny, Marc Schoenauer, Anne Auger:
Impacts of invariance in search: When CMA-ES and PSO face ill-conditioned and non-separable problems. Appl. Soft Comput. 11(8): 5755-5769 (2011) - [c46]Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
Analyzing the impact of mirrored sampling and sequential selection in elitist evolution strategies. FOGA 2011: 127-138 - [c45]Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
Mirrored sampling in evolution strategies with weighted recombination. GECCO 2011: 861-868 - [c44]Zyed Bouzarkouna, Anne Auger, Didier Yu Ding:
Local-meta-model CMA-ES for partially separable functions. GECCO 2011: 869-876 - [c43]Nikolaus Hansen, Anne Auger:
CMA-ES: evolution strategies and covariance matrix adaptation. GECCO (Companion) 2011: 991-1010 - [p1]Anne Auger, Nikolaus Hansen:
Theory of Evolution Strategies: A New Perspective. Theory of Randomized Search Heuristics 2011: 289-325 - [e3]Anne Auger, Benjamin Doerr:
Theory of Randomized Search Heuristics: Foundations and Recent Developments. Series on Theoretical Computer Science 1, World Scientific 2011, ISBN 978-981-4282-66-6 [contents] - 2010
- [j2]Anne Auger, Olivier Teytaud:
Continuous Lunches Are Free Plus the Design of Optimal Optimization Algorithms. Algorithmica 57(1): 121-146 (2010) - [c42]Zyed Bouzarkouna, Anne Auger, Didier Yu Ding:
Investigating the Local-Meta-Model CMA-ES for Large Population Sizes. EvoApplications (1) 2010: 402-411 - [c41]Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
Comparing the (1+1)-CMA-ES with a mirrored (1+2)-CMA-ES with sequential selection on the noiseless BBOB-2010 testbed. GECCO (Companion) 2010: 1543-1550 - [c40]Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
Mirrored variants of the (1, 2)-CMA-ES compared on the noiseless BBOB-2010 testbed. GECCO (Companion) 2010: 1551-1558 - [c39]Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
Mirrored variants of the (1, 4)-CMA-ES compared on the noiseless BBOB-2010 testbed. GECCO (Companion) 2010: 1559-1566 - [c38]Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
Mirrored variants of the (1, 2)-CMA-ES compared on the noisy BBOB-2010 testbed. GECCO (Companion) 2010: 1575-1582 - [c37]Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
Mirrored variants of the (1, 4)-CMA-ES compared on the noisy BBOB-2010 testbed. GECCO (Companion) 2010: 1583-1590 - [c36]Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
Investigating the impact of sequential selection in the (1, 2)-CMA-ES on the noiseless BBOB-2010 testbed. GECCO (Companion) 2010: 1591-1596 - [c35]Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
Investigating the impact of sequential selection in the (1, 4)-CMA-ES on the noiseless BBOB-2010 testbed. GECCO (Companion) 2010: 1597-1604 - [c34]Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
Investigating the impact of sequential selection in the (1, 2)-CMA-ES on the noisy BBOB-2010 testbed. GECCO (Companion) 2010: 1605-1610 - [c33]Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
Investigating the impact of sequential selection in the (1, 4)-CMA-ES on the noisy BBOB-2010 testbed. GECCO (Companion) 2010: 1611-1616 - [c32]Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
Benchmarking the (1, 4)-CMA-ES with mirrored sampling and sequential selection on the noiseless BBOB-2010 testbed. GECCO (Companion) 2010: 1617-1624 - [c31]Anne Auger, Dimo Brockhoff, Nikolaus Hansen:
Benchmarking the (1, 4)-CMA-ES with mirrored sampling and sequential selection on the noisy BBOB-2010 testbed. GECCO (Companion) 2010: 1625-1632 - [c30]Nikolaus Hansen, Anne Auger, Raymond Ros, Steffen Finck, Petr Posík:
Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009. GECCO (Companion) 2010: 1689-1696 - [c29]Dimo Brockhoff, Anne Auger, Nikolaus Hansen, Dirk V. Arnold, Tim Hohm:
Mirrored Sampling and Sequential Selection for Evolution Strategies. PPSN (1) 2010: 11-21 - [c28]Mohamed Jebalia, Anne Auger:
Log-Linear Convergence of the Scale-Invariant (µ/µw, lambda)-ES and Optimal µ for Intermediate Recombination for Large Population Sizes. PPSN (1) 2010: 52-62 - [c27]Anne Auger, Johannes Bader, Dimo Brockhoff:
Theoretically Investigating Optimal µ-Distributions for the Hypervolume Indicator: First Results for Three Objectives. PPSN (1) 2010: 586-596 - [e2]Anne Auger, Jonathan L. Shapiro, L. Darrell Whitley, Carsten Witt:
Theory of Evolutionary Algorithms, 05.09. - 10.09.2010. Dagstuhl Seminar Proceedings 10361, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Germany 2010 [contents] - [i6]Anne Auger, Jonathan L. Shapiro, L. Darrell Whitley, Carsten Witt:
10361 Abstracts Collection and Executive Summary - Theory of Evolutionary Algorithms. Theory of Evolutionary Algorithms 2010 - [i5]Anne Auger, Nikolaus Hansen, Jorge M. Perez Zerpa, Raymond Ros, Marc Schoenauer:
Experimental Comparisons of Derivative Free Optimization Algorithms. CoRR abs/1005.5631 (2010) - [i4]Zyed Bouzarkouna, Didier Yu Ding, Anne Auger:
Using Evolution Strategy with Meta-models for Well Placement Optimization. CoRR abs/1011.5481 (2010)
2000 – 2009
- 2009
- [c26]Anne Auger, Johannes Bader, Dimo Brockhoff, Eckart Zitzler:
Theory of the hypervolume indicator: optimal μ-distributions and the choice of the reference point. FOGA 2009: 87-102 - [c25]Anne Auger, Johannes Bader, Dimo Brockhoff, Eckart Zitzler:
Articulating user preferences in many-objective problems by sampling the weighted hypervolume. GECCO 2009: 555-562 - [c24]Anne Auger, Johannes Bader, Dimo Brockhoff, Eckart Zitzler:
Investigating and exploiting the bias of the weighted hypervolume to articulate user preferences. GECCO 2009: 563-570 - [c23]Anne Auger:
Benchmarking the (1+1) evolution strategy with one-fifth success rule on the BBOB-2009 function testbed. GECCO (Companion) 2009: 2447-2452 - [c22]Anne Auger:
Benchmarking the (1+1)-ES with one-fifth success rule on the BBOB-2009 noisy testbed. GECCO (Companion) 2009: 2453-2458 - [c21]Anne Auger, Nikolaus Hansen:
Benchmarking the (1+1)-CMA-ES on the BBOB-2009 function testbed. GECCO (Companion) 2009: 2459-2466 - [c20]Anne Auger, Nikolaus Hansen:
Benchmarking the (1+1)-CMA-ES on the BBOB-2009 noisy testbed. GECCO (Companion) 2009: 2467-2472 - [c19]Anne Auger, Raymond Ros:
Benchmarking the pure random search on the BBOB-2009 testbed. GECCO (Companion) 2009: 2479-2484 - [c18]Anne Auger, Raymond Ros:
Benchmarking the pure random search on the BBOB-2009 noisy testbed. GECCO (Companion) 2009: 2485-2490 - [c17]Anne Auger, Nikolaus Hansen, Jorge M. Perez Zerpa, Raymond Ros, Marc Schoenauer:
Experimental Comparisons of Derivative Free Optimization Algorithms. SEA 2009: 3-15 - [i3]Cyril Furtlehner, Jean-Marc Lasgouttes, Anne Auger:
Learning Multiple Belief Propagation Fixed Points for Real Time Inference. CoRR abs/0903.4860 (2009) - 2008
- [c16]Anne Auger, Nikolaus Hansen:
Evolution strategies and related estimation of distribution algorithms. GECCO (Companion) 2008: 2727-2740 - [c15]Mohamed Jebalia, Anne Auger:
On Multiplicative Noise Models for Stochastic Search. PPSN 2008: 52-61 - [e1]Dirk V. Arnold, Anne Auger, Jonathan E. Rowe, Carsten Witt:
Theory of Evolutionary Algorithms, 27.01. - 01.02.2008. Dagstuhl Seminar Proceedings 08051, Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany 2008 [contents] - [i2]Dirk V. Arnold, Anne Auger, Jonathan E. Rowe, Carsten Witt:
08051 Executive Summary - Theory of Evolutionary Algorithms. Theory of Evolutionary Algorithms 2008 - [i1]Dirk V. Arnold, Anne Auger, Carsten Witt, Jonathan E. Rowe:
08051 Abstracts Collection - Theory of Evolutionary Algorithms. Theory of Evolutionary Algorithms 2008 - 2007
- [c14]Mohamed Jebalia, Anne Auger, Pierre Liardet:
Log-Linear Convergence and Optimal Bounds for the (1+1)-ES. Artificial Evolution 2007: 207-218 - [c13]Olivier Teytaud, Anne Auger:
On the adaptation of noise level for stochastic optimization. IEEE Congress on Evolutionary Computation 2007: 3027-3034 - [c12]Mohamed Jebalia, Anne Auger, Marc Schoenauer, F. James, Marie Postel:
Identification of the isotherm function in chromatography using CMA-ES. IEEE Congress on Evolutionary Computation 2007: 4289-4296 - [c11]Anne Auger, Olivier Teytaud:
Continuous lunches are free! GECCO 2007: 916-922 - 2006
- [c10]Anne Auger, Nikolaus Hansen:
Reconsidering the progress rate theory for evolution strategies in finite dimensions. GECCO 2006: 445-452 - [c9]Nikolaus Hansen, Fabian Gemperle, Anne Auger, Petros Koumoutsakos:
When Do Heavy-Tail Distributions Help? PPSN 2006: 62-71 - 2005
- [j1]Anne Auger:
Convergence results for the (1, lambda)-SA-ES using the theory of phi-irreducible Markov chains. Theor. Comput. Sci. 334(1-3): 35-69 (2005) - [c8]Anne Auger, Mohamed Jebalia, Olivier Teytaud:
Algorithms (X, sigma, eta): Quasi-random Mutations for Evolution Strategies. Artificial Evolution 2005: 296-307 - [c7]Anne Auger, Nikolaus Hansen:
A restart CMA evolution strategy with increasing population size. Congress on Evolutionary Computation 2005: 1769-1776 - [c6]Anne Auger, Nikolaus Hansen:
Performance evaluation of an advanced local search evolutionary algorithm. Congress on Evolutionary Computation 2005: 1777-1784 - [c5]Anne Auger, Marc Schoenauer, Olivier Teytaud:
Local and global order 3/2 convergence of a surrogate evolutionary algorithm. GECCO 2005: 857-864 - 2004
- [b1]Anne Auger:
Contributions théoriques et numériques à l'optimisation continue par Algorithmes Evolutionnaires. Pierre and Marie Curie University, Paris, France, 2004 - [c4]Anne Auger, Marc Schoenauer, Nicolas Vanhaecke:
LS-CMA-ES: A Second-Order Algorithm for Covariance Matrix Adaptation. PPSN 2004: 182-191 - 2003
- [c3]Miguel Nicolau, Anne Auger, Conor Ryan:
Functional Dependency and Degeneracy: Detailed Analysis of the GAuGE System. Artificial Evolution 2003: 15-26 - [c2]Anne Auger, Claude Le Bris, Marc Schoenauer:
Dimension-Independent Convergence Rate for Non-isotropic (1, lambda) - ES. GECCO 2003: 512-524 - 2002
- [c1]Anne Auger, Adel Ben Haj Yedder, Marc Schoenauer:
Overview and software guide of evolutionary algorithms; A case study in quantum control. CRM Workshop 2002: 23-40
Coauthor Index
[j22] [c91] [i28] [j21] [c90] [c89] [j20] [j18] [c88] [c87] [j16] [j15] [c86] [c85] [j14] [j13] [j12] [c84] [c83] [c82] [i24] [i23] [c79] [i21] [j10] [c78] [c77] [c76] [c75] [j9] [c74] [c73] [c72] [c71] [c70] [c69] [c68] [c67] [c66] [c65] [c64] [i18] [i17] [i16] [i15] [i14] [j8] [c63] [p3] [c61] [c60] [c59] [c57] [p2] [i13] [c56] [c55] [c54] [i12] [i11] [j6] [c53] [c52] [c51] [c50] [c49] [c48] [c47] [i10] [i9] [i7] [j4] [j3] [c46] [c45] [c43] [p1] [c41] [c40] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [i5] [c21] [c20] [c17] [c16] [c10] [c9] [c7] [c6]
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