Team tao

Members
Overall Objectives
Scientific Foundations
Application Domains
Software
New Results
Contracts and Grants with Industry
Other Grants and Activities
Dissemination
Bibliography

Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

[1]
J. Bibai.
Segmentation et évolution pour la planification : le système Divide-And-Evolve, Université Paris Sud - Paris XI, October 2010.
http://hal.inria.fr/tel-00544407/en
[2]
A. Fialho.
Adaptive Selection of Operators and Heuristics for Optimization, Université Paris Sud - Paris XI, December 2010.
[3]
R. Gaudel.
Paramètres d'ordre et sélection de modèles en apprentissage : caractérisation des modèles et sélection d'attributs, Université Paris-Sud, December 2010.
[4]
N. Hansen.
Variable Metrics in Evolutionary Computation, HDR – Habilitation à Diriger des Recherches, Université Paris-Sud, February 2010, Ph. D. Thesis.
http://www.lri.fr/~hansen/hansen-habil-manu.pdf
[5]
J. Perez.
Apprentissage artificiel pour l'ordonnancement des tâches dans les grilles de calcul, Université Paris-Sud, September 2010.
[6]
P. Rolet.
Elements for Learning and Optimizing Expensive Functions, Université Paris-Sud, December 2010.
[7]
X. Zhang.
Contributions to Large Scale Data Clustering and Streaming with Affinity Propagation. Application to Autonomic Grids, Université Paris-Sud, July 2010.
http://tao.lri.fr/Papers/thesesTAO/ZhangPhD.pdf

Articles in International Peer-Reviewed Journal

[8]
A. Auger, J. Bader, D. Brockhoff, E. Zitzler.
Hypervolume-based Multiobjective Optimization: Theoretical Foundations and Practical Implications, in: Theoretical Computer Science, 2010, accepted.
[9]
P. Caillou, S. Aknine, S. Pinson.
Searching Pareto Optimal Solutions for the Problem of Forming and Restructuring Coalitions in Multi-Agent Systems, in: International Journal on Group Decision and Negotiation, 2010, 33 p.
http://hal.inria.fr/hal-00446087/en
[10]
P. Caillou, S. Aknine, S. Pinson.
Searching Pareto-optimal solutions for the problem of forming and restructuring coalitions in multi-agents systems, in: Group Decision and Negotiation, 2010, vol. 19, no 1, p. 7-37. [ DOI : 10.1007/s10726-009-9183-9 ]
http://hal.inria.fr/inria-00370430/en
[11]
P. Caillou, S. Aknine, S. Pinson.
Searching Pareto-optimal solutions for the problem of forming and restructuring coalitions in multi-agents systems, in: Group Decision and Negotiation, 2010, vol. 19, p. 7-37. [ DOI : 10.1007/s10726-009-9183-9 ]
http://hal.archives-ouvertes.fr/inria-00370430/en/
[12]
B. Cessac, H. Paugam-Moisy, T. Viéville.
Overview of facts and issues about neural coding by spikes, in: Journal of Physiology-Paris, 2010, vol. 104, no 1-2, p. 5-18. [ DOI : 10.1016/j.jphysparis.2009.11.002 ]
http://hal.inria.fr/inria-00407915/en
[13]
B. Cessac, H. Paugam-Moisy, T. Viéville.
Overview of facts and issues about neural coding by spikes, in: Journal of Physiology - Paris, 2010, vol. 104, p. 5-18.
http://hal.inria.fr/inria-00407915/en/
[14]
G. Chen, B. Kégl.
Invariant pattern recognition using contourlets and AdaBoost, in: Pattern Recognition, 2010, vol. 43, p. 579-583. [ DOI : 10.1016/j.patcog.2009.08.020 ]
http://hal.inria.fr/in2p3-00421717/en
[15]
Á. Fialho, L. Da Costa, M. Schoenauer, M. Sebag.
Analyzing bandit-based adaptive operator selection mechanisms, in: Annals of Mathematics and Artificial Intelligence - Special Issue on Learning and Intelligent Optimization, September 2010. [ DOI : 10.1007/s10472-010-9213-y ]
http://hal.inria.fr/inria-00519579/en
[16]
H. Fournier, O. Teytaud.
Lower Bounds for Comparison Based Evolution Strategies using VC-dimension and Sign Patterns, in: Algorithmica, 2010.
http://hal.inria.fr/inria-00452791/en
[17]
C. Furtlehner, M. Sebag, Z. Xiangliang.
Scaling Analysis of Affinity Propagation, in: Physical Review E: Statistical, Nonlinear, and Soft Matter Physics, June 2010, vol. 81, no 6, 066102 p. [ DOI : 10.1103/PhysRevE.81.066102 ]
http://hal.inria.fr/inria-00420407/en
[18]
M. Jebalia, A. Auger, N. Hansen.
Log linear convergence and divergence of the scale-invariant (1+1)-ES in noisy environments, in: Algorithmica, 2010.
http://hal.inria.fr/inria-00433347/en
[19]
J. Perez, C. Germain-Renaud, B. Kégl, C. Loomis.
Multi-objective reinforcement learning for responsive grids, in: Journal of Grid Computing, 2010, vol. 8, no 3, p. 473-492. [ DOI : 10.1007/s10723-010-9161-0 ]
http://hal.inria.fr/hal-00491560/en
[20]
A. Rimmel, O. Teytaud, C.-S. Lee, S.-J. Yen, M.-H. Wang, S.-R. Tsai.
Current Frontiers in Computer Go, in: IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games, 2010, in press p.
http://hal.inria.fr/inria-00544622/en

Articles in Non Peer-Reviewed Journal

[21]
J.-B. Hoock, C.-S. Lee, A. Rimmel, F. Teytaud, O. Teytaud, M.-H. Wang.
Intelligent Agents for the Game of Go, in: IEEE Computational Intelligence Magazine, November 2010.
http://hal.inria.fr/inria-00544758/en

International Peer-Reviewed Conference/Proceedings

[22]
A. Arbelaez, Y. Hamadi, M. Sebag.
Building Portfolios for the Protein Structure Prediction Problem, in: Workshop on Constraint Based Methods for Bioinformatics, Royaume-Uni Edinburgh, July 2010.
http://hal.inria.fr/inria-00515138/en
[23]
A. Arbelaez, Y. Hamadi, M. Sebag.
Continuous Search in Constraint Programming, in: 22th International Conference on Tools with Artificial Intelligence, France Arras, October 2010.
http://hal.inria.fr/inria-00515137/en
[24]
A. Arbelaez, Y. Hamadi, M. Sebag.
Continuous Search In Constraint Programming, in: Proc. 22nd ICTAI, 2010.
[25]
D. Arnold, N. Hansen.
Active Covariance Matrix Adaptation for the (1+1)-CMA-ES, in: Genetic And Evolutionary Computation Conference, États-Unis Portland, 2010, p. 385-392. [ DOI : 10.1145/1830483.1830556 ]
http://hal.inria.fr/hal-00503250/en
[26]
L. Arnold, H. Paugam-Moisy, M. Sebag.
Unsupervised Layer-Wise Model Selection in Deep Neural Networks, in: 19th European Conference on Artificial Intelligence (ECAI'10), Portugal Lisbon, August 2010, . p.
http://hal.inria.fr/hal-00488338/en
[27]
A. Auger, J. Bader, D. Brockhoff.
Theoretically Investigating Optimal $ \mu$ -Distributions for the Hypervolume Indicator: First Results For Three Objectives, in: Parallel Problem Solving from Nature (PPSN XI), Pologne Krakow, November 2010.
http://hal.inria.fr/inria-00534906/en
[28]
A. Auger, J. Bader, D. Brockhoff.
Theoretically Investigating Optimal $ \mu$ -Distributions for the Hypervolume Indicator: First Results For Three Objectives, in: Parallel Problem Solving from Nature (PPSN XI), R. Schaefer, et al. (editors), LNCS, Springer, 2010, vol. 6238, p. 586-595.
[29]
A. Auger, D. Brockhoff, N. Hansen.
Benchmarking the (1,4)-CMA-ES With Mirrored Sampling and Sequential Selection on the Noiseless BBOB-2010 Testbed, in: GECCO workshop on Black-Box Optimization Benchmarking (BBOB'2010), États-Unis Portland, OR, July 2010, p. 1617-1624. [ DOI : 10.1145/1830761.1830781 ]
http://hal.inria.fr/inria-00502439/en
[30]
A. Auger, D. Brockhoff, N. Hansen.
Benchmarking the (1,4)-CMA-ES With Mirrored Sampling and Sequential Selection on the Noisy BBOB-2010 Testbed, in: GECCO workshop on Black-Box Optimization Benchmarking (BBOB'2010), États-Unis Portland, OR, July 2010, p. 1625-1632. [ DOI : 10.1145/1830761.1830782 ]
http://hal.inria.fr/inria-00502441/en
[31]
A. Auger, D. Brockhoff, N. Hansen.
Comparing the (1+1)-CMA-ES with a Mirrored (1+2)-CMA-ES with Sequential Selection on the Noiseless BBOB-2010 Testbed, in: GECCO workshop on Black-Box Optimization Benchmarking (BBOB'2010), États-Unis Portland, OR, July 2010, p. 1543-1550. [ DOI : 10.1145/1830761.1830772 ]
http://hal.inria.fr/inria-00502430/en
[32]
A. Auger, D. Brockhoff, N. Hansen.
Investigating the Impact of Sequential Selection in the (1,2)-CMA-ES on the Noiseless BBOB-2010 Testbed, in: GECCO workshop on Black-Box Optimization Benchmarking (BBOB'2010), États-Unis Portland, OR, July 2010, p. 1591-1596. [ DOI : 10.1145/1830761.1830777 ]
http://hal.inria.fr/inria-00502431/en
[33]
A. Auger, D. Brockhoff, N. Hansen.
Investigating the Impact of Sequential Selection in the (1,2)-CMA-ES on the Noisy BBOB-2010 Testbed, in: GECCO workshop on Black-Box Optimization Benchmarking (BBOB'2010), États-Unis Portland, OR, July 2010, p. 1605–1610. [ DOI : 10.1145/1830761.1830779 ]
http://hal.inria.fr/inria-00502432/en
[34]
A. Auger, D. Brockhoff, N. Hansen.
Investigating the Impact of Sequential Selection in the (1,4)-CMA-ES on the Noiseless BBOB-2010 Testbed, in: GECCO workshop on Black-Box Optimization Benchmarking (BBOB'2010), États-Unis Portland, OR, July 2010, p. 1597-1604. [ DOI : 10.1145/1830761.1830778 ]
http://hal.inria.fr/inria-00502433/en
[35]
A. Auger, D. Brockhoff, N. Hansen.
Investigating the Impact of Sequential Selection in the (1,4)-CMA-ES on the Noisy BBOB-2010 Testbed, in: GECCO workshop on Black-Box Optimization Benchmarking (BBOB'2010), États-Unis Portland, OR, July 2010, p. 1611-1616. [ DOI : 10.1145/1830761.1830780 ]
http://hal.inria.fr/inria-00502434/en
[36]
A. Auger, D. Brockhoff, N. Hansen.
Mirrored Variants of the (1,2)-CMA-ES Compared on the Noiseless BBOB-2010 Testbed, in: GECCO workshop on Black-Box Optimization Benchmarking (BBOB'2010), États-Unis Portland, OR, July 2010, p. 1551-1558. [ DOI : 10.1145/1830761.1830772 ]
http://hal.inria.fr/inria-00502435/en
[37]
A. Auger, D. Brockhoff, N. Hansen.
Mirrored Variants of the (1,2)-CMA-ES Compared on the Noisy BBOB-2010 Testbed, in: GECCO workshop on Black-Box Optimization Benchmarking (BBOB'2010), États-Unis Portland, OR, July 2010, p. 1575-1582. [ DOI : 10.1145/1830761.1830775 ]
http://hal.inria.fr/inria-00502436/en
[38]
A. Auger, D. Brockhoff, N. Hansen.
Mirrored Variants of the (1,4)-CMA-ES Compared on the Noiseless BBOB-2010 Testbed, in: GECCO workshop on Black-Box Optimization Benchmarking (BBOB'2010), États-Unis Portland, OR, July 2010, p. 1559-1566. [ DOI : 10.1145/1830761.1830773 ]
http://hal.inria.fr/inria-00502437/en
[39]
A. Auger, D. Brockhoff, N. Hansen.
Mirrored Variants of the (1,4)-CMA-ES Compared on the Noisy BBOB-2010 Testbed, in: GECCO workshop on Black-Box Optimization Benchmarking (BBOB'2010), États-Unis Portland, OR, July 2010, p. 1583-1590. [ DOI : 10.1145/1830761.1830776 ]
http://hal.inria.fr/inria-00502438/en
[40]
A. Auger, D. Brockhoff, N. Hansen.
Analyzing the Impact of Mirrored Sampling and Sequential Selection in Elitist Evolution Strategies, in: Foundations of Genetic Algorithms (FOGA 2011), ACM, 2011, To appear.
[41]
R. Bardenet, B. Kégl.
Surrogating the surrogate: accelerating Gaussian-process-based global optimization with a mixture cross-entropy algorithm, in: International Conference on Machine Learning, June 2010, vol. 27, p. 55–62.
[42]
V. Berthier, H. Doghmen, O. Teytaud.
Consistency Modifications for Automatically Tuned Monte-Carlo Tree Search, in: Lion4, Italie venice, 2010, 14 p. p.
http://hal.inria.fr/inria-00437146/en
[43]
J. Bibai, P. Savéant, M. Schoenauer, V. Vidal.
On the Generality of Parameter Tuning in Evolutionary Planning, in: ACM Genetic and Evolutionary Computation Conference (GECCO-2010), États-Unis Portland, Oregon, July 2010, p. 241-248.
http://hal.inria.fr/inria-00463437/en
[44]
J. Bibai, P. Savéant, M. Schoenauer, V. Vincent.
An Evolutionary Metaheuristic for Domain-Independent Satisficing Planning, in: 20th International Conference on Automated Planning and Scheduling-ICAPS2010, Canada Toronto, R. Brafman, H. Geffner, J. Hoffmann, H. Kautz (editors), AAAI Press, May 2010, p. 15-25.
http://hal.inria.fr/inria-00456167/en
[45]
J. Bibai, P. Savéant, M. Schoenauer, V. Vincent.
On the Benefit of Sub-Optimality within the Divide-and-Evolve Scheme, in: 10th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP 2010 ), Turquie Istanbul, P. Merz, P. Cowling (editors), LNCS, Springer Verlag, May 2010, vol. 6022, p. 23-34. [ DOI : 10.1007/978-3-642-12139-5_3 ]
http://www.springerlink.com/content/d41267k850442518/, http://hal.inria.fr/inria-00443984/en
[46]
A. Bourki, G. Chaslot, M. Coulm, V. Danjean, H. Doghmen, T. Hérault, J.-B. Hoock, A. Rimmel, F. Teytaud, O. Teytaud, P. Vayssière, Z. Yu.
Scalability and Parallelization of Monte-Carlo Tree Search, in: The International Conference on Computers and Games 2010, Japon Kanazawa, 2010.
http://hal.inria.fr/inria-00512854/en
[47]
A. Bourki, M. Coulm, P. Rolet, O. Teytaud, P. Vayssière.
Parameter Tuning by Simple Regret Algorithms and Multiple Simultaneous Hypothesis Testing, in: ICINCO2010, Portugal funchal madeira, 2010, 10 p.
http://hal.inria.fr/inria-00467796/en
[48]
Z. Bouzarkouna, A. Auger, D. Y. Ding.
Investigating the Local-Meta-Model CMA-ES for Large Population Sizes, in: 3rd European event on Bio-inspired algorithms for continuous parameter optimisation (EvoNUM'10), Turquie Istanbul, C. D. Chio, S. Cagnoni, C. Cotta, M. Ebner, A. Ekárt, A. Esparcia-Alcázar, C. K. Goh, J. Juan (editors), Lecture Notes in Computer Science, April 2010, vol. 6024, p. 402-411.
http://hal.inria.fr/hal-00450238/en
[49]
Z. Bouzarkouna, D. Y. Ding, A. Auger.
Using Evolution Strategy with Meta–models for Well Placement Optimization, in: ECMOR XII – 12 th European Conference on the Mathematics of Oil Recovery, Royaume-Uni Oxford, EAGE (European Association of Geoscientists & Engineers), September 2010.
http://hal.inria.fr/inria-00538745/en
[50]
N. Bredeche, J.-M. Montanier.
Environment-driven Embodied Evolution in a Population of Autonomous Agents, in: Parallel Problem Solving From Nature, Pologne Krakow, 2010, p. 290–299.
http://hal.inria.fr/inria-00506771/en
[51]
N. Bredèche, E. Haasdijk, A. Eiben.
On-line, On-board Evolution of Robot Controllers, in: Artificial Evolution (EA'09) – Selected Papers, P. Collet, et al. (editors), LNCS 5975, Springer Verlag, 2010, p. 110-121.
[52]
D. Brockhoff, A. Auger, N. Hansen, D. Arnold, T. Hohm.
Mirrored Sampling and Sequential Selection for Evolution Strategies, in: PPSN, Pologne Warsaw, September 2010, p. 11-21.
http://hal.inria.fr/inria-00530202/en
[53]
D. Brockhoff.
Optimal $ \mu$ -Distributions for the Hypervolume Indicator for Problems With Linear Bi-Objective Fronts: Exact and Exhaustive Results, in: Simulated Evolution And Learning (SEAL-2010), Inde Kanpur, November 2010, corrected author version.
http://hal.inria.fr/inria-00534710/en
[54]
R. Busa-Fekete, B. Kégl.
Fast boosting using adversarial bandits, in: International Conference on Machine Learning, June 2010, vol. 27, p. 143–150.
[55]
R. Busa-Fekete, B. Kégl, T. Élteto, G. Szarvas.
Ranking by calibrated AdaBoost, in: Yahoo Ranking Challenge 2010 (JMLR workshop and conference proceedings), 2011.
[56]
P. Caillou.
Automated Multi-Agent Simulation Generation and Validation (Early Innovation), in: PRIMA 2010, Inde Calcutta, LNAI, November 2010.
http://hal.inria.fr/inria-00545253/en
[57]
P. Caillou.
Génération et analyse automatique de simulations multi-agents, in: JFSMA 2010, Tunisie Mahdia, October 2010.
http://hal.inria.fr/inria-00545251/en
[58]
S. Chevallier, H. Paugam-Moisy, M. Sebag.
SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system, in: NIPS'2010, Canada Vancouver, J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R. Zemel, A. Culott (editors), December 2010, p. 379–387.
http://hal.inria.fr/inria-00545669/en
[59]
S. Chevallier, H. Paugam-Moisy, M. Sebag.
SpikeAnts: a spiking neuron network modelling the emergence of organization in a complex system, in: Advances in Neural Information Processing Systems 23, Vancouver, December 2010, p. 114-119.
[60]
G. Collange, S. Reynaud, N. Hansen.
Covariance Matrix Adaptation Evolution Strategy for Multidisciplinary Optimization of Expendable Launcher Families, in: 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference, Proceedings, 2010.
[61]
R. Coulom, P. Rolet, N. Sokolovska, O. Teytaud.
Handling Expensive Optimization with Large Noise, in: Foundations of Genetic Algorithms (FOGA 2011), H.-G. Beyer, W. Langdon (editors), 01 2011, To appear.
http://hal.archives-ouvertes.fr/hal-00517157/en/
[62]
P. Delarboulas, M. Schoenauer, M. Sebag.
Open-Ended Evolutionary Robotics: an Information Theoretic Approach, in: PPSN XI, Pologne Krakow, R. Schaefer, et al. (editors), LNCS, Springer Verlag, 2010, p. 334-342.
http://hal.inria.fr/inria-00494237/en
[63]
T. Elteto, C. Germain-Renaud, P. Bondon, M. Sebag.
Discovering Piecewise Linear Models of Grid Workload, in: 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, Australie Melbourne, IEEE Computer Society, May 2010, p. 474-484.
http://hal.inria.fr/hal-00491562/en
[64]
A. Fialho, W. Gong, Z. Cai.
Probability Matching-based Adaptive Strategy Selection vs. Uniform Strategy Selection within Differential Evolution, in: Workshop Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 2010, p. 1527-1534.
[65]
Á. Fialho, R. Ros, M. Schoenauer, M. Sebag.
Comparison-based Adaptive Strategy Selection with Bandits in Differential Evolution, in: 11th International Conference on Parallel Problem Solving From Nature - PPSN, Pologne Krakow, September 2010.
http://hal.inria.fr/inria-00493005/en
[66]
Á. Fialho, M. Schoenauer, M. Sebag.
Fitness-AUC Bandit Adaptive Strategy Selection vs. the Probability Matching one within Differential Evolution: An Empirical Comparison on the BBOB-2010 Noiseless Testbed, in: GECCO 2010 Workshop on Black-Box Optimization Benchmarking, États-Unis Portland, July 2010.
http://hal.inria.fr/inria-00494535/en
[67]
Á. Fialho, M. Schoenauer, M. Sebag.
Toward Comparison-based Adaptive Operator Selection, in: Genetic and Evolutionary Computation Conference (GECCO), États-Unis Portland, ACM, 2010.
http://hal.inria.fr/inria-00471264/en
[68]
C. Furtlehner, Y. Han, J.-M. Lasgouttes, V. Martin, F. Marchal, F. Moutarde.
Spatial and Temporal Analysis of Traffic States on Large Scale Networks, in: 13th International IEEE Conference on Intelligent Transportation Systems ITSC'2010, Portugal Madère, September 2010, - p.
http://hal.inria.fr/hal-00527481/en
[69]
R. Gaudel, J.-B. Hoock, J. Pérez, N. Sokolovska, O. Teytaud.
A Principled Method for Exploiting Opening Books, in: International Conference on Computers and Games, Japon Kanazawa, 2010.
http://hal.inria.fr/inria-00484043/en
[70]
R. Gaudel, M. Sebag.
Feature Selection as a One-Player Game, in: International Conference on Machine Learning, Israël Haifa, 2010, p. 359–366.
http://hal.inria.fr/inria-00484049/en
[71]
C. Germain-Renaud, A. Cady.
Performance evaluation of the Estimated Response Time strategy: tools, methods and an experiment, in: EGEE User Forum, Suède Uppsala, April 2010.
http://hal.inria.fr/inria-00544441/en
[72]
W. Gong, A. Fialho, Z. Cai.
Adaptive Strategy Selection in Differential Evolution, in: GECCO, J. Branke, et al. (editors), ACM Press, July 2010, p. 409-416.
[73]
N. Hansen, A. Auger, R. Ros, S. Finck, P. Posík.
Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009, in: GECCO (Companion), J. Branke, et al. (editors), ACM, July 2010, p. 1689–1696.
[74]
N. Hansen, R. Ros.
Benchmarking a Weighted Negative Covariance Matrix Update on the BBOB-2010 Noiseless Testbed, in: Genetic And Evolutionary Computation Conference, États-Unis Portland, 2010, p. 1673-1680. [ DOI : 10.1145/1830761.1830788 ]
http://hal.inria.fr/hal-00545728/en
[75]
N. Hansen, R. Ros.
Benchmarking a weighted negative covariance matrix update on the BBOB-2010 noiseless testbed, in: GECCO (Companion), J. Branke, et al. (editors), ACM, July 2010, p. 1673–1680.
[76]
N. Hansen, R. Ros.
Benchmarking a weighted negative covariance matrix update on the BBOB-2010 noisy testbed, in: GECCO (Companion), J. Branke, et al. (editors), ACM, July 2010, p. 1681–1688.
[77]
J.-B. Hoock, O. Teytaud.
Bandit-Based Genetic Programming, in: 13th European Conference on Genetic Programming, Turquie Istanbul, Springer, 2010.
http://hal.inria.fr/inria-00452887/en
[78]
M. Jebalia, A. Auger.
Log-linear Convergence of the Scale-invariant ($ \mu$/$ \mu$_w, $ \lambda$) -ES and Optimal $ \mu$ for Intermediate Recombination for Large Population Sizes, in: Parallel Problem Solving From Nature (PPSN2010), Pologne Krakow, R. Schaefer, C. Cotta, J. Kolodziej, G. Rudolph (editors), Lecture Notes in Computer Science, Springer, 2010, p. xxxx-xxx.
http://hal.inria.fr/inria-00494478/en
[79]
A. Katsifodimos, J.-D. Fekete, A. Cady, C. Germain-Renaud.
Visualizing the dynamics of e-science social networks, in: EGEE User Forum, 2010.
http://hal.inria.fr/inria-00544452/en
[80]
I. Loshchilov, M. Schoenauer, M. Sebag.
A Mono Surrogate for Multiobjective Optimization, in: Genetic and Evolutionary Computation Conference 2010 (GECCO), J. Branke, et al. (editors), 2010.
http://hal.inria.fr/inria-00483948/en
[81]
I. Loshchilov, M. Schoenauer, M. Sebag.
Comparison-Based Optimizers Need Comparison-Based Surrogates, in: Parallel Problem Solving from Nature XI (PPSN 2010), Pologne Krakow, September 2010.
http://hal.inria.fr/inria-00493921/en
[82]
I. Loshchilov, M. Schoenauer, M. Sebag.
Dominance-Based Pareto-Surrogate for Multi-Objective Optimization, in: Simulated Evolution And Learning (SEAL-2010), Inde Kanpur, October 2010.
http://hal.inria.fr/inria-00522653/en
[83]
A. Mouraud, H. Paugam-Moisy, A. Guillaume.
The DAMNED Simulator for Implementing a Dynamic Model of the Network Controlling Saccadic Eye Movements, in: ICANN'2010, International Conference on Artificial Neural Networks, Grèce Thessaloniki, September 2010.
http://hal.inria.fr/inria-00545670/en
[84]
A. Mouraud, A. Guillaume, H. Paugam-Moisy.
The DAMNED simulator for implementing a dynamic model of the network controlling saccadic eye movements, in: ICANN'2010, International Conference on Artificial Neural Networks, Thessaloniki, LNCS, Lecture Notes in Computer Science, Springer, 2010, vol. 6352, p. 272-281.
[85]
M. Nicolau, M. Schoenauer, W. Banzhaf.
Evolving Genes to Balance a Pole, in: European Conference on Genetic Programming, Turquie Istanbul, A. Esparcia-Alcazar, et al. (editors), LNCS, Springer Verlag, 2010, vol. 6021, p. 196-207.
http://hal.inria.fr/inria-00483681/en
[86]
A. Rimmel, F. Teytaud.
Multiple Overlapping Tiles for Contextual Monte Carlo Tree Search, in: Evostar, Turquie Istanbul, February 2010.
http://hal.inria.fr/inria-00456422/en
[87]
A. Rimmel, F. Teytaud, O. Teytaud.
Biasing Monte-Carlo Simulations through RAVE Values, in: The International Conference on Computers and Games 2010, Japon Kanazawa, May 2010.
http://hal.inria.fr/inria-00485555/en
[88]
P. Rolet, O. Teytaud.
Adaptive Noisy Optimization, in: EvoStar 2010, Turquie Istambul, February 2010.
http://hal.inria.fr/inria-00459017/en
[89]
P. Rolet, O. Teytaud.
Bandit-based Estimation of Distribution Algorithms for Noisy Optimization: Rigorous Runtime Analysis, in: Lion4, Italie Venice, 2010.
http://hal.inria.fr/inria-00437140/en
[90]
P. Rolet, O. Teytaud.
Complexity Bounds for Batch Active Learning in Classification, in: Machine Learning and Knowledge Discovery in Databases, J. Balcázar, F. Bonchi, A. Gionis, M. Sebag (editors), Lecture Notes in Computer Science, Springer Berlin / Heidelberg, 2010, vol. 6323, p. 293-305.
http://hal.inria.fr/inria-00533318/en
[91]
R. Ros, N. Hansen.
Black-Box Optimization Benchmarking of NEWUOA compared to BIPOP-CMA-ES, in: Genetic and Evolutionary Computation Conference 2010, États-Unis Portland, OR, April 2010, – p.
http://hal.inria.fr/inria-00473779/en
[92]
R. Ros.
Black-Box Optimization Benchmarking the IPOP-CMA-ES on the Noiseless Testbed, in: Genetic and Evolutionary Computation Conference 2010, États-Unis Portland, OR, April 2010, – p.
http://hal.inria.fr/inria-00473777/en
[93]
R. Ros.
Black-Box Optimization Benchmarking the IPOP-CMA-ES on the Noisy Testbed, in: Genetic and Evolutionary Computation Conference 2010, États-Unis Portland, OR, April 2010.
http://hal.inria.fr/inria-00473778/en
[94]
R. Ros.
Comparison of NEWUOA with Different Numbers of Interpolation Points on the BBOB Noiseless Testbed, in: Genetic and Evolutionary Computation Conference 2010, États-Unis Portland, OR, April 2010.
http://hal.inria.fr/inria-00473774/en
[95]
R. Ros.
Comparison of NEWUOA with Different Numbers of Interpolation Points on the BBOB Noisy Testbed, in: Genetic and Evolutionary Computation Conference 2010, États-Unis Portland, OR, April 2010.
http://hal.inria.fr/inria-00473776/en
[96]
F. Teytaud.
A new selection ratio for large population sizes, in: Evostar, Turquie Istanbul, February 2010.
http://hal.inria.fr/inria-00456335/en
[97]
F. Teytaud, O. Teytaud.
Log(lambda) Modifications for Optimal Parallelism, in: Parallel Problem Solving From Nature, Pologne Krakow, September 2010.
http://hal.inria.fr/inria-00495087/en
[98]
F. Teytaud, O. Teytaud.
On the Huge Benefit of Decisive Moves in Monte-Carlo Tree Search Algorithms, in: IEEE Conference on Computational Intelligence and Games, Danemark Copenhagen, August 2010.
http://hal.inria.fr/inria-00495078/en
[99]
T. Voß, N. Hansen, C. Igel.
Improved Step Size Adaptation for the MO-CMA-ES, in: Genetic And Evolutionary Computation Conference, États-Unis Portland, ACM, 2010, p. 487-494. [ DOI : 10.1145/1830483.1830573 ]
http://hal.inria.fr/hal-00503251/en
[100]
X. Zhang, C. Germain-Renaud, M. Sebag.
Adaptively Detecting Changes in Autonomic Grid Computing, in: Procs of ACS 2010, Belgique, October 2010.
http://wiki.esi.ac.uk/ACS2010, http://hal.inria.fr/hal-00540579/en

National Peer-Reviewed Conference/Proceedings

[101]
L. Arnold, H. Paugam-Moisy, M. Sebag.
Optimisation de la Topologie pour les Réseaux de Neurones Profonds, in: 17e congrès francophone AFRIF-AFIA Reconnaissance des Formes et Intelligence Artificielle - RFIA 2010, France Caen, January 2010, . p.
http://hal.inria.fr/hal-00437538/en
[102]
S. Chevallier, H. Paugam-Moisy, M. Sebag.
SpikeAnts : un réseau de neurones impulsionnels pour modéliser l'émergence de l'organisation, in: Cinquième conférence française de Neurosciences Computationnelles, France Lyon, October 2010, p. 114-119.
http://2010.neurocomp.fr/neurocomp10proceedings.pdf, http://hal.inria.fr/inria-00529514/en
[103]
S. Chevallier, H. Paugam-Moisy, M. Sebag.
SpikeAnts : un réseau de neurones impulsionnels pour modéliser l'émergence de l'organisation, in: 5th french conference in computational neurosciences, NeuroComp'10, Lyon, October 2010, p. 114-119.

Workshops without Proceedings

[104]
C. Furtlehner, M. Schoenauer.
Multi-Objective 3-SAT with Survey-Propagation, in: NIPS 2010 Workshop on Discrete Optimization in Machine Learning: Structures, Algorithms and Applications (DISCML), Canada Whisler, November 2010.
http://hal.inria.fr/inria-00533149/en
[105]
I. Loshchilov, M. Schoenauer, M. Sebag.
A Pareto-Compliant Surrogate Approach for Multiobjective Optimization, in: Genetic and Evolutionary Computation Conference 2010 (GECCO-2010), États-Unis Portland, OR, July 2010.
http://hal.inria.fr/hal-00483996/en
[106]
M. Samsonov, C. Furtlehner, J.-M. Lasgouttes.
Exactly Solvable Stochastic Processes for Traffic Modelling, in: 25th International Symposium on Computer and Information Sciences - ISCIS 2010, Royaume-Uni Londres, September 2010.
http://hal.inria.fr/inria-00533154/en

Scientific Books (or Scientific Book chapters)

[107]
G. Collange, N. Delattre, N. Hansen, I. Quinquis, M. Schoenauer.
Multidisciplinary Optimisation in the Design of Future Space Launchers, in: Multidisciplinary Design Optimization in Computational Mechanics, P. Breitkopf, R. F. Coelho (editors), Wiley, 2010, chap. 12, p. 487–496.
[108]
Y. Collette, N. Hansen, G. Pujol, D. Salazar Aponte, R. Le Riche.
On Object-Oriented Programming of Optimizers – Examples in Scilab, in: Multidisciplinary Design Optimization in Computational Mechanics, R. F. Coelho, P. Breitkopf (editors), Wiley, 2010.
http://hal.inria.fr/inria-00476172/en
[109]
A. Eiben, E. Haasdijk, N. Bredeche.
Embodied, On-line, On-board Evolution for Autonomous Robotics, in: Symbiotic Multi-Robot Organisms: Reliability, Adaptability, Evolution., P. Levi, S. Kernbach (editors), Series: Cognitive Systems Monographs, Springer, 2010, vol. 7, p. 361-382.
http://hal.inria.fr/inria-00531455/en
[110]
A. Eiben, E. Haasdijk, N. Bredeche.
Embodied, On-line, On-board Evolution for Autonomous Robotics, in: Symbiotic Multi-Robot Organisms: Reliability, Adaptability, Evolution., P. Levi, S. Kernbach (editors), Series: Cognitive Systems Monographs, Springer, 2010, vol. 7, p. 361-382.
http://hal.inria.fr/inria-00531455/en/
[111]
J. Maturana, A. Fialho, F. Saubion, M. Schoenauer, F. Lardeux, M. Sebag.
Adaptive Operator Selection and Management in Evolutionary Algorithms, in: Autonomous Search, Y. Hamadi, et al (editors), Springer Verlag, 2010, To appear.

Books or Proceedings Editing

[112]
A. Auger, B. Doerr (editors)
Theory of Randomized Seach Heuristics–Foundations and Recent Developments, Theoretical Computer Science, World Scientific, 2010, vol. 1.

Internal Reports

[113]
A. Auger, D. Brockhoff, N. Hansen.
Mirrored Sampling and Sequential Selection for Evolution Strategies, INRIA, April 2010, no RR-7249.
http://hal.inria.fr/inria-00472650/en
[114]
A. Auger, S. Finck, N. Hansen, R. Ros.
BBOB 2009: Comparison Tables of All Algorithms on All Noiseless Functions, INRIA, April 2010, no RT-0383.
http://hal.inria.fr/inria-00471251/en
[115]
A. Auger, S. Finck, N. Hansen, R. Ros.
BBOB 2009: Comparison Tables of All Algorithms on All Noisy Functions, INRIA, April 2010, no RT-0384.
http://hal.inria.fr/inria-00471253/en
[116]
A. Auger, S. Finck, N. Hansen, R. Ros.
BBOB 2010: Comparison Tables of All Algorithms on All Noiseless Functions, INRIA, September 2010, no RT-388.
http://hal.inria.fr/inria-00516689/en
[117]
A. Auger, S. Finck, N. Hansen, R. Ros.
BBOB 2010: Comparison Tables of All Algorithms on All Noisy Functions, INRIA, September 2010, no RT-389.
http://hal.inria.fr/inria-00516690/en
[118]
N. Beume, D. Brockhoff.
Summary of the First GECCO Workshop on Theoretical Aspects of Evolutionary Multiobjective Optimization, INRIA, November 2010, no RR-7444.
http://hal.inria.fr/inria-00533367/en
[119]
D. Brockhoff, A. Auger, F. Marchal.
Calibrating Traffic Simulations as an Application of CMA-ES in Continuous Blackbox Optimization: First Results, INRIA, 2010, no RR-7304.
http://hal.inria.fr/inria-00496596/en
[120]
Á. Fialho, R. Ros.
Analysis of Adaptive Strategy Selection within Differential Evolution on the BBOB-2010 Noiseless Benchmark, INRIA, April 2010, no RR-7259.
http://hal.inria.fr/inria-00476160/en
[121]
C. Furtlehner, M. Schoenauer.
Multi Objective 3-SAT Problems addressed with Message Passing Techniques, INRIA, October 2010, no RR-7424.
http://hal.inria.fr/inria-00528438/en
[122]
N. Hansen, A. Auger, S. Finck, R. Ros.
Real-Parameter Black-Box Optimization Benchmarking 2010: Experimental Setup, INRIA, March 2010, no RR-7215.
http://hal.inria.fr/inria-00462481/en
[123]
M. Jebalia, A. Auger.
Log-linear Convergence of the Scale-invariant ($ \mu$/$ \mu$_w, $ \lambda$) -ES and Optimal mu for Intermediate Recombination for Large Population Sizes, INRIA, June 2010, no RR-7275.
http://hal.inria.fr/inria-00495401/en
[124]
M. Samsonov, C. Furtlehner, J.-M. Lasgouttes.
Exactly Solvable Stochastic Processes for Traffic Modelling, INRIA, May 2010, no RR-7278.
http://hal.inria.fr/inria-00492430/en

Other Publications

[125]
Y. Ollivier, C. Villani.
A curved Brunn-Minkowski inequality on the discrete hypercube, 2010.
http://hal.inria.fr/inria-00540479/en

References in notes

[126]
A. Arbelaez, Y. Hamadi, M. Sebag.
Online Heuristic Selection in Constraint Programing, in: International Symposium on Combinatorial Search, 2009.
[127]
B. Frey, D. Dueck.
Clustering by passing messages between data points, in: Science, 2007, vol. 315, p. 972–976.
[128]
S. Gelly, O. Teytaud.
Opendp: a free reinforcement learning toolbox for discrete time control problems, in: NIPS Workshop on Machine Learning Open Source Software, 2006.
[129]
J. O. Kephart, D. M. Chess.
The vision of autonomic computing, in: Computer, 2003, vol. 36, p. 41-50.
[130]
J.-M. Montanier, N. Bredèche.
Embedded Evolutionary Robotics: The (1+1)-Restart-Online Adaptation Algorithm, in: CD Proceedings of IROS 2009 Workshop on Exploring new horizons in Evolutionary Design of Robots (Evoderob09), 2009, p. 37-43.
[131]
G. Moore.
Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Customer, Collins Business Essentials, 1991.
[132]
I. Rechenberg.
Evolutionstrategie: Optimierung Technisher Systeme nach Prinzipien des Biologischen Evolution, Fromman-Hozlboog Verlag, 1973.
[133]
I. Rish, M. Brodie, S. Ma, N. Odintsova, A. Beygelzimer, G. Grabarnik, K. Hernandez.
daptive diagnosis in distributed dystems, in: IEEE Transactions on Neural Networks (special issue on Adaptive Learning Systems in Communication Networks), 2005, vol. 16, p. 1088-1109.
[134]
M. Schoenauer, P. Savéant, V. Vidal.
Divide-and-Evolve: a New Memetic Scheme for Domain-Independent Temporal Planning, in: 8th European Conf. on Evolutionary Computation in Combinatorial Optimization (EvoCOP'06), Budapest, J. Gottlieb, G. Raidl (editors), LNCS, Springer Verlag, 2006, no 3906, p. 247-260.
http://hal.inria.fr/inria-00000975/en/

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