Project Team Tao

Members
Overall Objectives
Scientific Foundations
Application Domains
Software
New Results
Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography
PDF e-pub XML


Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

[1]
A. Arbelaez.
Learning During Search, Université Paris-Sud XI, Orsay - France, May 2011.
[2]
F. Teytaud.
Introduction of Statistics in Optimization, Universite Paris-Sud XI, Orsay - France, December 2011.
[3]
O. Teytaud.
Artificial Intelligence and Optimization with parallelism, Univeristé Paris-Sud, April 2011, Habilitation à Diriger des Recherches.

Articles in International Peer-Reviewed Journal

[4]
A. Auger, J. Bader, D. Brockhoff, E. Zitzler.
Hypervolume-based Multiobjective Optimization: Theoretical Foundations and Practical Implications, in: Theoretical Computer Science, December 2011. [ DOI : 10.1016/j.tcs.2011.03.012 ]
http://hal.inria.fr/inria-00638989/en
[5]
D. Auger, O. Teytaud.
The Frontier of Decidability in Partially Observable Recursive Games, in: International Journal on Fundations of Computer Science, 2012, Accepted.
[6]
Z. Bouzarkouna, D. Y. Ding, A. Auger.
Well Placement Optimization with the Covariance Matrix Adaptation Evolution Strategy and Meta-Models, in: Computational Geosciences, September 2011, p. 1-18.
http://hal.inria.fr/hal-00628126/en
[7]
N. Bredeche, J.-M. Montanier, W. Liu, A. Winfield.
Environment-driven Distributed Evolutionary Adaptation in a Population of Autonomous Robotic Agents, in: Mathematical and Computer Modelling of Dynamical Systems, 2011.
http://hal.inria.fr/inria-00531450/en
[8]
A. Devert, N. Bredeche, M. Schoenauer.
Robustness and the Halting Problem for Multi-Cellular Artificial Ontogeny, in: IEEE Transactions on Evolutionary Computation, 2011.
http://hal.inria.fr/inria-00566879/en
[9]
T. Elteto, C. Germain-Renaud, P. Bondon, M. Sebag.
Towards Non-Stationary Grid Models, in: Journal of Grid Computing, December 2011. [ DOI : 10.1007/s10723-011-9194-z ]
http://hal.inria.fr/inria-00616279/en
[10]
G. Fouquier, J. Atif, I. Bloch.
Sequential model-based segmentation and recognition of image structures driven by visual features and spatial relations, in: Computer Vision and Image Understanding, 2011, accepted, toappear.
[11]
N. Hansen, R. Ros, N. Mauny, M. Schoenauer, A. Auger.
Impacts of Invariance in Search: When CMA-ES and PSO Face Ill-Conditioned and Non-Separable Problems, in: Applied Soft Computing, 2011, vol. 11, p. 5755-5769. [ DOI : 10.1016/j.asoc.2011.03.001 ]
http://hal.inria.fr/inria-00583669/en

International Conferences with Proceedings

[12]
R. Akrour, M. Schoenauer, M. Sebag.
Preference-Based Policy Learning, in: Machine Learning and Knowledge Discovery in Databases, D. Gunopulos, T. Hofmann, D. Malerba, M. Vazirgiannis (editors), LNCS, Springer Verlag, 2011, vol. 6911, p. 12-27.
http://hal.inria.fr/inria-00625001/en
[13]
A. Arbelaez, Y. Hamadi.
Improving Parallel Local Search for SAT, in: Learning and Intelligent Optimization, Fifth International Conference, LION 2011, Coello Coelle, Carlos A. (editor), LNCS 6683, Springer Verlag, 2011, p. 46-60.
[14]
J. Atif, C. Hudelot, I. Bloch.
Abduction in Description Logics using Formal Concept Analysis and Mathematical Morphology: application to image interpretation, in: Concept Lattices and Applications (CLA2011), Nancy, Paris, October 2011, p. 405-408.
[15]
I. Atsonios, O. Beaumont, N. Hanusse, Y. Kim.
On Power-Law Distributed Balls in Bins and its Applications to View Size Estimation, in: ISAAC, Yokohama, Japan, December 2011.
http://hal.inria.fr/inria-00618785/en
[16]
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), Schwarzenberg, Austria, April 2011, p. 127-138. [ DOI : 10.1145/1967654.1967666 ]
http://hal.inria.fr/inria-00587507/en
[17]
A. Auger, D. Brockhoff, N. Hansen.
Mirrored Sampling in Evolution Strategies With Weighted Recombination, in: Genetic and Evolutionary Computation Conference (GECCO 2011), Dublin, Ireland, ACM, July 2011, p. 861-868. [ DOI : 10.1145/2001576.2001694 ]
http://hal.inria.fr/inria-00612522/en
[18]
J. Bergstra, R. Bardenet, Y. Bengio, B. Kégl.
Algorithms for Hyper-Parameter Optimization, in: 25th Annual Conference on Neural Information Processing Systems (NIPS 2011), Granada, Spain, November 2011.
http://hal.inria.fr/hal-00642998/en
[19]
Best Paper
Z. Bouzarkouna, A. Auger, D. Y. Ding.
Local-Meta-Model CMA-ES for Partially Separable Functions, in: Genetic and Evolutionary Computation Conference (GECCO 2011), Dublin, Ireland, July 2011, p. 869-876.
http://hal.inria.fr/hal-00588977/en
[20]
Z. Bouzarkouna, D. Y. Ding, A. Auger.
Partially Separated Meta-models with Evolution Strategies for Well Placement Optimization, in: 73rd EAGE Conference & Exhibition incorporating SPE EUROPEC, Vienne, Austria, May 2011.
http://hal.inria.fr/hal-00588983/en
[21]
R. Busa-Fekete, B. Kégl, T. Elteto, G. Szarvas.
A Robust Ranking Methodology based on Diverse Calibration of AdaBoost, in: European Conference on Machine Learning (ECML 2011), Athens, Greece, November 2011.
http://hal.inria.fr/hal-00643000/en
[22]
R. Busa-Fekete, B. Kégl, T. Elteto, G. Szarvas.
Ranking by calibrated AdaBoost, in: Yahoo! Learning to Rank Challenge, Haifa, Israel, June 2011.
http://hal.inria.fr/hal-00643001/en
[23]
S. Chevallier, N. Bredeche, H. Paugam-Moisy, M. Sebag.
Emergence of Temporal and Spatial Synchronous Behaviors in a Foraging Swarm, in: ECAL 2011, Paris, France, T. Lenaerts, M. Giacobini, H. Bersini, P. Bourgine, M. Dorigo, R. Doursat (editors), LCNS, Springer, August 2011, p. 125-132.
[24]
C.-W. Chou, P.-C. Chou, H. Doghmen, C.-S. Lee, T.-C. Su, F. Teytaud, O. Teytaud.
Towards a solution of 7x7 Go with Meta-MCTS, in: Proc. Advances in Computer Games, 2011, Accepted.
[25]
P.-C. Chou, H. Doghmen, C.-S. Lee, F. Teytaud, O. Teytaud, H.-C. Wang, M.-H. Wang, S.-J. Yen, W.-L. Wu.
Computational and Human Intelligence in Blind Go, in: Computational Intelligence and Games, Seoul, Korea, Democratic People'S Republic Of, September 2011.
http://hal.inria.fr/inria-00625849/en
[26]
C.-W. Chou, O. Teytaud, S.-J. Yen.
Revisiting Monte-Carlo Tree Search on a Normal Form Game: NoGo, in: EvoGames 2011, Turino, Italy, Lecture Notes in Computer Science, Springer-Verlag, April 2011, vol. 6624, p. 73-82. [ DOI : 10.1007/978-3-642-20525-5 ]
http://hal.inria.fr/inria-00593154/en
[27]
R. Coulom, P. Rolet, N. Sokolovska, O. Teytaud.
Handling Expensive Optimization with Large Noise, in: Foundations of Genetic Algorithms, Austria, ACM, January 2011, p. 61-68.
http://hal.inria.fr/hal-00517157/en
[28]
A. Couëtoux, J.-B. Hoock, N. Sokolovska, O. Teytaud, N. Bonnard.
Continuous Upper Confidence Trees, in: LION'11: Proc. 5th International Conference on Learning and Intelligent OptimizatioN, Italy, LNCS 6683, Springer Verlag, January 2011, p. 433-445.
http://hal.inria.fr/hal-00542673/en
[29]
A. Couëtoux, M. Milone, M. Brendel, H. Doghmen, M. Sebag, O. Teytaud.
Continuous Rapid Action Value Estimates, in: The 3rd Asian Conference on Machine Learning (ACML2011), Taoyuan, Taiwan, Province Of China, C.-N. Hsu, W. S. Lee (editors), Workshop and Conference Proceedings, JMLR, 2011, vol. 20, p. 19-31.
http://hal.inria.fr/hal-00642459/en
[30]
A. Couëtoux, M. Milone, O. Teytaud.
Consistent Belief State Estimation, with Application to Mines, in: Proc. TAAI 2011, 2011.
[31]
A. Couëtoux, O. Teytaud, H. Doghmen.
Improving exploration in Upper Confidence Trees, in: Proc. LION'6, Y. Hamadi, M. Schoenauer (editors), LNCS, Springer Verlag, 2012.
[32]
S. Cussat-Blanc, N. Bredeche, H. Luga, Y. Duthen, M. Schoenauer.
Artificial Gene Regulatory Network and Spatial Computation: A Case Study, in: European Conference on Artificial Life, Paris, France, 2011.
http://hal.inria.fr/inria-00601778/en
[33]
S. Cussat-Blanc, N. Bredeche, H. Luga, Y. Duthen, M. Schoenauer.
Artificial Gene Regulatory Networks and Spatial Computation: A Case Study, in: ECAL, Paris, France, August 2011.
http://hal.inria.fr/inria-00601816/en
[34]
Á. Fialho, Y. Hamadi, M. Schoenauer.
Optimizing Architectural and Structural Aspects of Buildings towards Higher Energy Efficiency, in: GECCO 2011 Workshop on GreenIT Evolutionary Computation, Dublin, Ireland, July 2011.
http://hal.inria.fr/inria-00591930/en
[35]
C. Furtlehner, Y. Han, J.-M. Lasgouttes, V. Martin, F. Moutarde.
Propagation of information on undirected dependency graphs for road traffic inference, in: Chaos, Complexity and Transport, CCT'11, Marseille, France, 2011.
http://hal.inria.fr/hal-00648681/en/
[36]
C. Furtlehner, J.-M. Lasgouttes, M. Samsonov.
The Fundamental Diagram on the Ring Geometry for Particle Processes with Acceleration/Braking Asymmetry, in: Traffic and Granular Flow 2011, Moscou, Russie, Fédération De, 2011.
http://hal.inria.fr/hal-00646988/en/
[37]
C. Germain-Renaud, A. Cady, P. Gauron, M. Jouvin, C. Loomis, J. Martyniak, J. Nauroy, G. Philippon, M. Sebag.
The Grid Observatory, in: IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, Newport Beach, United States, IEEE Computer Society Press, May 2011.
http://hal.inria.fr/inria-00586502/en
[38]
C. Germain-Renaud, F. Fürst, M. Jouvin, G. Kassel, J. Nauroy, G. Philippon.
The Green Computing Observatory: a data curation approach for green IT, in: International Conference on Cloud and Green Computing, Sydney, Australia, December 2011.
http://hal.inria.fr/inria-00632423/en
[39]
V. Heidrich-Meisner, C. Igel.
Non-linearly increasing resampling in racing algorithms, in: European Symposium on Artificial Neural Networks, Bruges, Belgium, M. Verleysen (editor), Evere, Belgium: d-side publications, April 2011, p. 465-470.
http://hal.inria.fr/inria-00633006/en
[40]
B. Helmstetter, C.-S. Lee, F. Teytaud, O. Teytaud, M.-H. Wang, S.-J. Yen.
Random positions in Go, in: Computational Intelligence and Games, Seoul, Korea, Democratic People'S Republic Of, September 2011.
http://hal.inria.fr/inria-00625815/en
[41]
J.-B. Hoock, O. Teytaud.
Progress Rate in Noisy Genetic Programming for Choosing λ, in: Artificial Evolution, Angers, France, J.-K. Hao, et al. (editors), 2011.
http://hal.inria.fr/inria-00622150/en
[42]
Y. Kim, C. Germain-Renaud.
Characterizing E-Science File Access Behavior via Latent Dirichlet Allocation, in: 4th IEEE International Conference on Utility and Cloud Computing (UCC 2011), Melbourne, Australia, IEEE, December 2011.
http://hal.inria.fr/inria-00617914/en
[43]
A. Kuno, J.-M. Montanier, S. Takano, N. Bredeche, M. Schoenauer, M. Sebag, E. Suzuki.
On-board Evolutionary Algorithm and Off-line Rule Discovery for Column Formation in Swarm Robotics, in: IEEE/ACM/WIC International Conference on Intelligent Agent Technology, Lyon, France, 2011.
http://hal.inria.fr/inria-00601785/en
[44]
Z. Lewkovicz, S. Thiriot, P. Caillou.
How detailed should social networks be for labor market's models ?, in: SNAMAS@AISB 2011, York, United Kingdom, April 2011.
http://hal.inria.fr/inria-00579620/en
[45]
I. Loshchilov, M. Schoenauer, M. Sebag.
Adaptive Coordinate Descent, in: Genetic and Evolutionary Computation Conference (GECCO 2011), Dublin, Ireland, April 2011.
http://hal.inria.fr/inria-00587534/en
[46]
I. Loshchilov, M. Schoenauer, M. Sebag.
Not all parents are equal for MO-CMA-ES, in: Evolutionary Multi-Criterion Optimization 2011 (EMO 2011), Ouro Preto, Brazil, February 2011.
http://hal.inria.fr/inria-00565282/en
[47]
D. Lupin Saint-Pierre, Q. Louveaux, O. Teytaud.
Online Sparse Bandit for Card Games, in: Proc. Advances in Computer Games, 2011, Accepted.
[48]
D. Lupin Saint-Pierre, Q. Louveaux, O. Teytaud.
Online Sparse Bandits, in: The 3rd Asian Conference on Machine Learning (ACML2011), Taoyuan, Taiwan, Province Of China, 2011.
http://hal.inria.fr/hal-00642461/en
[49]
B. Matthias, M. Schoenauer.
Instance-Based Parameter Tuning and Learning for Evolutionary AI Planning, in: Workshop on Planning and Learning at 21st ICAPS, Freiburg, Germany, June 2011.
http://hal.inria.fr/inria-00632368/en
[50]
B. Matthias, M. Schoenauer.
Instance-based parameter tuning for evolutionary AI planning, in: Workshops Proc. of Genetic and Evolutionary Computation Conference, Dublin, Ireland, ACM Press, July 2011, p. 591-599.
http://hal.inria.fr/inria-00632375/en
[51]
B. Matthias, M. Schoenauer.
Learn-and-Optimize: a Parameter Tuning Framework for Evolutionary AI Planning, in: Artificial Evolution, Angers, France, J.-K. Hao, et al. (editors), October 2011.
http://hal.inria.fr/inria-00632378/en
[52]
J.-M. Montanier, N. Bredeche.
Emergence of Altruism in Open-ended Evolution in a Population of Autonomous Agents, in: GECCO, Dublin, Ireland, 2011.
http://hal.inria.fr/inria-00601791/en
[53]
J.-M. Montanier, N. Bredeche.
Surviving the Tragedy of Commons: Emergence of Altruism in a Population of Evolving Autonomous Agents, in: European Conference on Artificial Life, Paris, France, 2011.
http://hal.inria.fr/inria-00601776/en
[54]
J. Perez, B. Kégl, C. Germain-Renaud.
Non-Markovian Reinforcement Learning for Reactive Grid scheduling, in: Conférence Francophone d'Apprentissage, Chambéry, France, Presses Universitaires des Antilles et de la Guyane (editor), Publibook, May 2011.
http://hal.inria.fr/inria-00586504/en
[55]
S. Rebecchi, H. Paugam-Moisy, M. Sebag.
Learning sparse features with an auto-associator, in: DevLeaNN, 2011.
[56]
A. Rimmel, F. Teytaud, T. Cazenave.
Optimization of the Nested Monte-Carlo Algorithm on the Traveling Salesman Problem with Time Windows, in: Evostar, Turin, Italy, February 2011.
http://hal.inria.fr/inria-00563668/en
[57]
T. Runarsson, M. Schoenauer, M. Sebag.
Pilot, Rollout and Monte Carlo Tree Search Methods for Combinatorial Optimization, in: Proc. LION'6, Y. Hamadi, M. Schoenauer (editors), LNCS, Springer Verlag, 2012.
[58]
M. Schoenauer, F. Teytaud, O. Teytaud.
A Rigorous Runtime Analysis for Quasi-Random Restarts and Decreasing Stepsize, in: Artificial Evolution, Angers, France, J.-K. Hao, et al. (editors), October 2011.
http://hal.inria.fr/inria-00625855/en
[59]
N. Sokolovska.
Aspects of Semi-Supervised and Active Learning in Conditional Random Fields, in: ECML PKDD 2011, Greece, September 2011, p. 273-288.
http://hal.inria.fr/hal-00624831/en
[60]
N. Sokolovska, O. Teytaud, M. Milone.
Q-Learning with Double Progressive Widening : Application to Robotics, in: ICONIP 2011, China, September 2011, p. 103-112.
http://hal.inria.fr/hal-00624832/en
[61]
O. Teytaud, S. Flory.
Upper Confidence Trees with Short Term Partial Information, in: EvoGames 2011, Turino, Italy, Lecture Notes in Computer Science, Springer, 2011, vol. 6624, p. 153-162. [ DOI : 10.1007/978-3-642-20525-5 ]
http://hal.inria.fr/inria-00585475/en
[62]
O. Teytaud, M. Sebag.
Combining Myopic Optimization and Tree Search: Application to MineSweeper, in: Proc. LION'6, Y. Hamadi, M. Schoenauer (editors), LNCS, Springer Verlag, 2012.
[63]
F. Teytaud, O. Teytaud.
Lemmas on Partial Observation, with Application to Phantom Games, in: Computational Intelligence and Games, Seoul, Korea, Democratic People'S Republic Of, September 2011.
http://hal.inria.fr/inria-00625794/en
[64]
S. Thiriot, Z. Lewkovicz, P. Caillou, J.-D. Kant.
Referral hiring and labor markets: a computational study, in: Artificial Economics 2011, The Hague, Netherlands, S. Osinga, G. J. Hofstede, T. Verwaart (editors), LNEMS, Springer-Verlag, September 2011, vol. 652, p. 15-25.
http://hal.inria.fr/inria-00579625/en
[65]
M. Yagoubi, L. Thobois, M. Schoenauer.
Asynchronous Evolutionary Multi-Objective Algorithms with heterogeneous evaluation costs, in: IEEE Congress on Evolutionary Computation, CEC 2011, New Orleans, LA, United States, June 2011, p. 21-28.
http://hal.inria.fr/hal-00625318/en

National Conferences with Proceeding

[66]
J. Atif, C. Hudelot, I. Bloch.
Abduction dans les logiques de description : apport de l'analyse formelle de concepts et de la morphologie mathématique, in: Représentation et Raisonnement sur le Temps et l'Espace (Atelier RTE 2011), Chambery, France, May 2011, p. 405-408.
[67]
N. Galichet, M. Sebag.
Exploration prudente: une approche par méthode de Monte-Carlo arborescente contrainte, in: Proc. Reconnaissance des Formes et Intelligence Artificielle, January 2012, to appear.
[68]
C. Germain-Renaud.
Modèles comportementaux de la grille : enjeux et exemples, in: Premières journées scientifiques France-Grilles, Lyon, France, September 2011.
http://hal.inria.fr/inria-00632438/en

Conferences without Proceedings

[69]
R. Bardenet, B. Kégl, G. Fort.
Relabelling MCMC Algorithms in Bayesian Mixture Learning, in: Snowbird Learning Workshop, Fort Lauderdale, United States, April 2011.
http://hal.inria.fr/in2p3-00590956/en
[70]
P. Caillou, E.-P. Gallié, V. Mérindol, T. Weil.
Caractérisation et typologie du contexte initial des pôles, in: 7e congrés de l'Académie de l'entrepreneuriat et de l'innovation, Paris, France, October 2011.
http://hal.inria.fr/hal-00653037/en/
[71]
A. Couëtoux, O. Teytaud, N. Bonnard, N. Omont, O. Ratier.
Monte Carlo Tree Search appliqué à la gestion de stocks, in: ROADEF 2011, France, March 2011, p. N241, p.I-149.
http://hal.inria.fr/hal-00623668/en
[72]
E.-P. Gallié, V. Mérindol, P. Caillou, T. Weil.
Les pôles de compétitivité français en fonction de leur contexte initial d'émergence : essai de caractérisation, in: EvoReg 2011, Strasbourg, France, October 2011.
http://hal.inria.fr/hal-00653036/en/
[73]
X. Zhou, P. Caillou, J. Gil-Quijano.
Automated observation of complex systems simulations, in: V2CS 2011, Paris, France, November 2011.
http://hal.inria.fr/hal-00644639/en

Scientific Books (or Scientific Book chapters)

[74]
A. Arbelaez, Y. Hamadi, M. Sebag.
Continuous Search in Constraint Programming, in: Autonomous Search, Y. Hamadi, E. Monfroy, F. Saubion (editors), Springer-Verlag, 2011.
[75]
S. Doncieux, N. Bredeche, J.-B. Mouret.
New Horizons in Evolutionary Robotics, Springer, 2011.
http://hal.inria.fr/inria-00566890/en
[76]
S. Doncieux, J.-B. Mouret, N. Bredeche, V. Padois.
Evolutionary Robotics: Exploring New Horizons, in: New Horizons in Evolutionary Robotics, Studies in Computational Intelligence, Springer, 2011, p. 3-25.
http://hal.inria.fr/inria-00566896/en
[77]
J.-K. Hao, P. Legrand, P. Collet, N. Monmarché, E. Lutton, M. Schoenauer.
Artificial Evolution 2011, LNCS, Springer Verlag, 2012, To appear.
http://hal.inria.fr/hal-00643404/en
[78]
J.-M. Montanier, N. Bredeche.
Embedded Evolutionary Robotics: The (1+1)-Restart-Online Adaptation Algorithm, in: New Horizons in Evolutionary Robotics, Studies in Computational Intelligence, Springer, 2011, p. 155-169.
http://hal.inria.fr/inria-00566898/en
[79]
O. Teytaud.
Lower Bounds for Evolution Strategies, in: Theory of Randomized Search Heuristics, A. Auger, B. Doerr (editors), Series on Theoretical Computer Science, World Scientific, May 2011, vol. 1, p. 327-354.
http://hal.inria.fr/inria-00593179/en

Internal Reports

[80]
N. Hansen, S. Finck, R. Ros.
COCO - COmparing Continuous Optimizers : The Documentation, INRIA, May 2011, no RT-0409.
http://hal.inria.fr/inria-00597334/en
[81]
N. Hansen.
A CMA-ES for Mixed-Integer Nonlinear Optimization, INRIA, October 2011, no RR-7751.
http://hal.inria.fr/inria-00629689/en
[82]
N. Hansen.
Injecting External Solutions Into CMA-ES, INRIA, October 2011, no RR-7748.
http://hal.inria.fr/inria-00628254/en
[83]
V. Martin, J.-M. Lasgouttes, C. Furtlehner.
The Role of Normalization in the Belief Propagation Algorithm, INRIA, January 2011, no RR-7514.
http://hal.inria.fr/inria-00558444/en

Other Publications

[84]
R. Akrour, M. Schoenauer, M. Sebag.
Preference-based Reinforcement Learning, 2011, NIPS Workshop on Choice Models and Preference Learning.
[85]
L. Arnold, A. Auger, N. Hansen, Y. Ollivier.
Information-Geometric Optimization Algorithms: A Unifying Picture via Invariance Principles, 2011, submitted.
http://hal.inria.fr/hal-00601503/en
[86]
D. Auger.
Multiple Tree for Partially Observable Monte-Carlo Tree Search, 2011, submitted.
http://hal.inria.fr/hal-00563480/en
[87]
E. Descamps, C. Furtlehner, M. Schoenauer.
, 2011, Work in progress.
[88]
C. Furtlehner, J.-M. Lasgouttes, M. Samsonov.
One-dimensional Particle Processes with Acceleration/Braking Asymmetry, 2011, arXiv:1109.1761, submitted to J. Stat. Phys..
[89]
V. Martin, C. Furtlehner, J.-M. Lasgouttes.
Encoding Dependencies between real-valued observables with a binary latent MRF, 2011, submitted to AISTAT.
References in notes
[90]
C. Candan, J. Dréo, P. Savéant, V. Vidal.
Parallel Divide-and-Evolve: Experiments with OpenMP on a Multicore Machine, in: Proc. GECCO, N. Kranogor (editor), ACM Press, 2011, p. 1571-1579.
[91]
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.
[92]
B. Frey, D. Dueck.
Clustering by passing messages between data points, in: Science, 2007, vol. 315, p. 972–976.
[93]
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/
[94]
J. O. Kephart, D. M. Chess.
The vision of autonomic computing, in: Computer, 2003, vol. 36, p. 41-50.
[95]
C.-S. Lee, M.-H. Wang, O. Teytaud, Y.-L. Wang.
The Game of Go @ IEEE WCCI 2010, in: IEEE Computational Intelligence Magazine, 2010, vol. 5, no 4, p. 6-7. [ DOI : 10.1109/MCI.2010.938371 ]
http://hal.inria.fr/inria-00632302/en/
[96]
K. Li, Á. Fialho, S. Kwong.
Multi-Objective Differential Evolution with Adaptive Control of Parameters and Operators, in: LION'11: Proceedings of the 5th International Conference on Learning and Intelligent OptimizatioN, C. A. Coello Coello (editor), LNCS 6683, Springer Verlag, January 2011, p. 473-4887.
[97]
G. Moore.
Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Customer, Collins Business Essentials, 1991.
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