Project-Team Tao
Members
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography
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Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 5Y. Akimoto, S. Astete-Morales, O. Teytaud.
    Analysis of runtime of optimization algorithms for noisy functions over discrete codomains, in: Journal of Theoretical Computer Science (TCS), 2015, vol. 605, 42:50 p. [ DOI : 10.1016/j.tcs.2015.04.008 ]
    https://hal.inria.fr/hal-01194556
  • 6S. Astete-Morales, M.-L. Cauwet, J. Liu, O. Teytaud.
    Simple and Cumulative Regret for Continuous Noisy Optimization, in: Journal of Theoretical Computer Science (TCS), 2015, vol. 617, pp. 12–27.
    https://hal.inria.fr/hal-01194564
  • 7R. Bardenet, O.-A. Maillard.
    Concentration inequalities for sampling without replacement, in: Bernoulli, 2015, vol. 21, no 3, pp. 1361-1385. [ DOI : 10.3150/14-BEJ605 ]
    https://hal.archives-ouvertes.fr/hal-01216652
  • 8M.-L. Cauwet, J. Liu, R. Baptiste, O. Teytaud.
    Algorithm Portfolios for Noisy Optimization, in: Annals of Mathematics and Artificial Intelligence, November 2015, pp. 1-30. [ DOI : 10.1007/s10472-015-9486-2 ]
    https://hal.archives-ouvertes.fr/hal-01223113
  • 9G. Charpiat, G. Nardi, G. Peyré, F.-X. Vialard.
    Piecewise rigid curve deformation via a Finsler steepest descent, in: Interfaces and Free Boundaries, December 2015.
    https://hal.archives-ouvertes.fr/hal-00849885
  • 10A. Chotard, A. Auger, N. Hansen.
    Markov Chain Analysis of Cumulative Step-size Adaptation on a Linear Constrained Problem, in: Evolutionary Computation, 2015, vol. 23, no 4, pp. 611-640. [ DOI : 10.1109/4235.873238 ]
    https://hal.inria.fr/hal-01215727
  • 11A. Decelle, P. Zhang.
    Inference of the sparse kinetic Ising model using the decimation method, in: Physical Review E : Statistical, Nonlinear, and Soft Matter Physics, May 2015, vol. 91, no 5. [ DOI : 10.1103/PhysRevE.91.052136 ]
    https://hal.archives-ouvertes.fr/hal-01250830
  • 12D. Feng, C. Germain.
    Fault monitoring with sequential matrix factorization, in: ACM Transactions on Autonomous and Adaptive Systems, 2015, vol. 10, no 3, pp. 20:1–20:25. [ DOI : 10.1145/2797141 ]
    https://hal.inria.fr/hal-01176013
  • 13V. Martin, J.-M. Lasgouttes, C. Furtlehner.
    Latent binary MRF for online reconstruction of large scale systems, in: Annals of Mathematics and Artificial Intelligence, 2015, pp. 1-32. [ DOI : 10.1007/s10472-015-9470-x ]
    https://hal.inria.fr/hal-01186220
  • 14Y. Ollivier.
    Riemannian metrics for neural networks I: Feedforward networks, in: Information and Inference, 2015, vol. 4, no 2, pp. 108–153. [ DOI : 10.1093/imaiai/iav006 ]
    https://hal.archives-ouvertes.fr/hal-00857982
  • 15Y. Ollivier.
    Riemannian metrics for neural networks II: Recurrent networks and learning symbolic data sequences, in: Information and Inference, 2015, vol. 4, no 2, pp. 154–193. [ DOI : 10.1093/imaiai/iav007 ]
    https://hal.archives-ouvertes.fr/hal-00857980
  • 16Y. Shogo, M. Ohzeki, A. Decelle.
    Detection of Cheating by Decimation Algorithm, in: Journal of the Physical Society of Japan, January 2015, vol. 84, 024801. [ DOI : 10.7566/JPSJ.84.024801 ]
    https://hal.archives-ouvertes.fr/hal-01105415
  • 17N. Sokolovska, O. Teytaud, S. Rizkalla, K. Clément, J.-D. Zucker.
    Sparse Zero-Sum Games as Stable Functional Feature Selection, in: PLoS ONE, September 2015, vol. 10, no 9, MicroObese consortium, e0134683. [ DOI : 10.1371/journal.pone.0134683 ]
    http://hal.upmc.fr/hal-01223887

Invited Conferences

  • 18F. Hutter, B. Kégl, R. Caruana, I. Guyon, H. Larochelle, E. Viegas.
    Automatic Machine Learning (AutoML), in: ICML 2015 Workshop on Resource-Efficient Machine Learning, 32nd International Conference on Machine Learning, Lille, France, July 2015.
    http://hal.in2p3.fr/in2p3-01171463

International Conferences with Proceedings

  • 19E. Alberts, G. Charpiat, Y. Tarabalka, T. Huber, M.-A. Weber, J. Bauer, C. Zimmer, B. H. Menze.
    A Nonparametric model for Brain Tumor Segmentation and Volumetry in Longitudinal MR Sequences, in: MICCAI Brain Lesion Workshop, Munich, Germany, October 2015.
    https://hal.inria.fr/hal-01205916
  • 20S. Astete-Morales, M.-L. Cauwet, O. Teytaud.
    Evolution Strategies with Additive Noise: A Convergence Rate Lower Bound, in: Foundations of Genetic Algorithms, Aberythswyth, United Kingdom, ACM, 2015, pp. 76–84.
    https://hal.inria.fr/hal-01077625
  • 21N. Belkhir, J. Dréo, P. Savéant, M. Schoenauer.
    Parameter Setting for Multicore CMA-ES with Large Populations, in: Artificial Evolution (EA 2015), Lyon, France, S. Bonnevay, P. Legrand, N. Montmarché, E. Lutton, M. Schoenauer (editors), Springer Verlag, October 2015, forthcoming.
    https://hal.inria.fr/hal-01236025
  • 22V. Berthier.
    Comparing optimizers on a unit commitment problem, in: Artificial Evolution (EA2015), Lyon, France, S. Bonnevay, P. Legrand, N. Montmarché, E. Lutton, M. Schoenauer (editors), Springer Verlag, October 2015, forthcoming.
    https://hal.inria.fr/hal-01215804
  • 23V. Berthier.
    Experiments on the CEC 2015 expensive optimization testbed, in: CEC 2015 - IEEE Congress on Evolutionary Computation, Sendai, Japan, IEEE Press, May 2015, pp. 1059 - 1066. [ DOI : 10.1109/CEC.2015.7257007 ]
    https://hal.inria.fr/hal-01215805
  • 24V. Berthier.
    Progressive Differential Evolution on Clustering Real World Problems, in: EA 2015 - International Conference on Artificial Evolution, Lyon, France, Springer, October 2015.
    https://hal.inria.fr/hal-01215803
  • 25V. Berthier, A. Couëtoux, O. Teytaud.
    Combining policies: the best of human expertise and neurocontrol, in: Artificial Evolution 2015 (EA2015), Lyon, France, 2015, forthcoming.
    https://hal.inria.fr/hal-01194516
  • 26V. Berthier, O. Teytaud.
    On the codimension of the set of optima: large scale optimisation with few relevant variables, in: Artificial Evolution 2015, Lyon, France, Proceedings of Artificial Evolution 2015 (EA2015), 2015, forthcoming.
    https://hal.inria.fr/hal-01194519
  • 27V. Berthier, O. Teytaud.
    Sieves method in fuzzy control: logarithmically increase the number of rules, in: IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Istanbul, Turkey, IEEE Press, August 2015, pp. 1 - 9.
    https://hal.inria.fr/hal-01215806
  • 28D. Brockhoff, T.-D. Tran, N. Hansen.
    Benchmarking Numerical Multiobjective Optimizers Revisited, in: Genetic and Evolutionary Computation Conference (GECCO 2015), Madrid, Spain, A. Esparcia, S. Silva (editors), July 2015, pp. 639-646. [ DOI : 10.1145/2739480.2754777 ]
    https://hal.inria.fr/hal-01146741
  • 29P. Caillou, B. Gaudou, A. Grignard, C. Q. Truong, P. Taillandier.
    A Simple-to-use BDI architecture for Agent-based Modeling and Simulation, in: The Eleventh Conference of the European Social Simulation Association (ESSA 2015), Groningen, Netherlands, September 2015.
    https://hal.inria.fr/hal-01216165
  • 30M.-L. Cauwet, O. Teytaud, S.-Y. Chiu, K.-M. Lin, S.-J. Yen, D. L. Saint-Pierre, F. Teytaud.
    Parallel Evolutionary Algorithms Performing Pairwise Comparisons, in: Foundations of Genetic Algorithms, Aberythswyth, United Kingdom, J. He, T. Jansen, G. Ochoa, C. Zarges (editors), ACM, 2015, pp. 99-113.
    https://hal.inria.fr/hal-01077626
  • 31M.-L. Cauwet, O. Teytaud, H.-M. Liang, S.-J. Yen, H.-H. Lin, I.-C. Wu, T. Cazenave, A. Saffidine.
    Depth, balancing, and limits of the Elo model, in: IEEE Conference on Computational Intelligence and Games 2015, Tainan, Taiwan, I, August 2015.
    https://hal.archives-ouvertes.fr/hal-01223116
  • 32T. Cazenave, J. Liu, O. Teytaud.
    The Rectangular Seeds of Domineering, Atari-Go and Breakthrough, in: 2015 IEEE Conference on Computational Intelligence and Games (CIG), Tainan, Taiwan, August 2015, pp. 530 - 531. [ DOI : 10.1109/CIG.2015.7317904 ]
    https://hal.inria.fr/hal-01245531
  • 33S.-Y. Chiu, C.-N. Lin, J. Liu, T.-C. Su, F. Teytaud, O. Teytaud, S.-J. Yen.
    Differential Evolution for Strongly Noisy Optimization: Use 1.01n Resamplings at Iteration n and Reach the -1/2 Slope, in: 2015 IEEE Congress on Evolutionary Computation (IEEE CEC), Sendai, Japan, May 2015.
    https://hal.inria.fr/hal-01120892
  • 34S.-Y. Chiu, C.-N. Lin, J. Liu, T.-C. Su, F. Teytaud, O. Teytaud, S.-J. Yen.
    Differential evolution for strongly noisy optimization: Use 1.01n resamplings at iteration n and reach the − 1/2 slope, in: 2015 IEEE Congress on Evolutionary Computation (IEEE CEC 2015), Sendai, Japan, May 2015, pp. 338 - 345. [ DOI : 10.1109/CEC.2015.7256911 ]
    https://hal.inria.fr/hal-01245526
  • 35J.-J. Christophe, J. Decock, J. Liu, O. Teytaud.
    Variance Reduction in Population-Based Optimization: Application to Unit Commitment, in: Artificial Evolution (EA2015), Lyon, France, S. Bonnevay, P. Legrand, N. Montmarché, E. Lutton, M. Schoenauer (editors), 2015, forthcoming.
    https://hal.inria.fr/hal-01194510
  • 36J. Decock, D. L. Saint-Pierre, O. Teytaud.
    Evolutionary Cutting Planes, in: Artificial Evolution (EA2015), Lyon, France, S. Bonnevay, P. Legrand, N. Montmarché, E. Lutton, M. Schoenauer (editors), 2015, forthcoming.
    https://hal.inria.fr/hal-01194540
  • 37C. Faur, P. Caillou, J.-C. Martin, C. Clavel.
    A Socio-cognitive Approach to Personality: Machine-learned Game Strategies as Cues of Regulatory Focus, in: Affective Computing and Intelligent Interaction (ACII 2015), Xi'an, China, September 2015.
    https://hal.inria.fr/hal-01216540
  • 38R. Ffrancon, M. Schoenauer.
    Greedy Semantic Local Search for Small Solutions, in: Companion Proceedings (workshops) of the Genetic and Evolutionary Computation COnference, TAO, Inria Saclay, France, July 2015, pp. 1293-1300.
    https://hal.inria.fr/hal-01169075
  • 40E. Galván-López, M. Schoenauer, C. Patsakis.
    Design of an Autonomous Intelligent Demand-Side Management System by using Electric Vehicles as Mobile Energy Storage Units by Means of Evolutionary Algorithms, in: 7th International Joint Conference on Computational Intelligence (IJCCI 2015), Lisbon, Portugal, A. C. Rosa, J. J. M. Guervós, A. Dourado, J. M. Cadenas, K. Madani, A. E. Ruano, J. Filipe (editors), SciTePress, November 2015, vol. 1, pp. 106–115. [ DOI : 10.5220/0005607401060115 ]
    https://hal.inria.fr/hal-01254912
  • 41G. Grefenstette, L. Muchemi.
    Extracting Hierarchical Topic Models from the Web for Improving Digital Archive Access, in: Expert Workshop on Topic Models and Corpus Analysis, Dublin, Ireland, DARIAH Text & Data Analytics Working Group, December 2015.
    https://hal.inria.fr/hal-01251326
  • 42E. Maggiori, Y. Tarabalka, G. Charpiat.
    Improved Partition Trees for Multi-Class Segmentation of Remote Sensing Images, in: 2015 IEEE International Geoscience and Remote Sensing Symposium - IGARSS 2015, Milan, Italy, IEEE, July 2015.
    https://hal.inria.fr/hal-01182772
  • 43E. Maggiori, Y. Tarabalka, G. Charpiat.
    Optimizing Partition Trees for Multi-Object Segmentation with Shape Prior, in: 26th British Machine Vision Conference, Swansea, United Kingdom, September 2015.
    https://hal.inria.fr/hal-01182776
  • 44L. Malagò, G. Pistone.
    Information Geometry of Gaussian Distributions in View of Stochastic Optimization, in: Foundations of Genetic Algorithms XIII, Aberystwyth, United Kingdom, ACM, January 2015, pp. 150-162.
    https://hal.inria.fr/hal-01108986
  • 45W. Mei-Hui, C.-S. Wang, C.-S. Lee, O. Teytaud, J. Liu, S.-W. Lin, P.-H. Hung.
    Item response theory with fuzzy markup language for parameter estimation and validation, in: 2015 IEEE Conference on Fuzzy Systems (FUZZ-IEEE), Istanbul, Turkey, IEEE Press, August 2015, pp. 1 - 7. [ DOI : 10.1109/FUZZ-IEEE.2015.7337884 ]
    https://hal.inria.fr/hal-01245695
  • 46Y. Ollivier.
    Laplace's rule of succession in information geometry, in: Geometric science of information, Palaiseau, France, F. Nielsen, F. Barbarescro (editors), LNCS, Springer Verlag, October 2015, vol. 9389, pp. 311-319.
    https://hal.archives-ouvertes.fr/hal-01228952
  • 47A. Quemy, M. Schoenauer.
    True Pareto Fronts for Multi-Objective AI Planning Instances, in: European Conference on Combinatorial Optimization - EvoCOP, Copenhague, Denmark, F. Chicano, G. Ochoa (editors), LNCS 9026, Springer Verlag, April 2015, pp. 197-208.
    https://hal.archives-ouvertes.fr/hal-01109777
  • 48A. Quemy, M. Schoenauer, V. Vidal, J. Dréo, P. Savéant.
    Solving Large MultiZenoTravel Benchmarks with Divide-and-Evolve, in: Learning and Intelligent OptimizatioN - LION 9, Lille, France, C. Dhaenens, L. Jourdan, M.-E. Marmion (editors), LNCS 8994, Springer Verlag, January 2015, pp. 262-267.
    https://hal.archives-ouvertes.fr/hal-01109776
  • 49K. Rafes, J. Nauroy, C. Germain.
    Certifying the interoperability of RDF database systems, in: LDQ 2015 - 2nd Workshop on Linked Data Quality, Portorož, Slovenia, Springer, May 2015, no 2.
    https://hal.inria.fr/hal-01147765
  • 50A. Saffidine, O. Teytaud, S.-J. Yen.
    Go Complexities, in: Advances in Computer Games, Leiden, Netherlands, 2015. [ DOI : 10.1007/978-3-319-27992-3_8 ]
    https://hal.inria.fr/hal-01256660
  • 51D. L. St-Pierre, J. Liu, O. Teytaud.
    Nash Reweighting of Monte Carlo Simulations: Tsumego, in: 2015 IEEE Congress on Evolutionary Computation (IEEE CEC 2015), Sendai, Japan, IEEE Press, May 2015, pp. 1458 - 1465. [ DOI : 10.1109/CEC.2015.7257060 ]
    https://hal.inria.fr/hal-01245520
  • 52O. Teytaud.
    Quasi-random numbers improve the CMA-ES on the BBOB testbed, in: Artificial Evolution (EA2015), Lyon, France, S. Bonnevay, P. Legrand, N. Montmarché, E. Lutton, M. Schoenauer (editors), Springer Verlag, 2015, 13 p, forthcoming.
    https://hal.inria.fr/hal-01194542

National Conferences with Proceedings

  • 53I. Brigui-Chtioui, P. Caillou, S. Pinson.
    Approche Anytime pour l'ajustement de l'incrément dans les enchères multicritères automatisées, in: 23es Journées Francophones sur les Systèmes Multi-Agents (JFSMA'15), Rennes, France, L. Vercouter, G. Picard (editors), Cépaduès, June 2015, pp. 153-162.
    https://hal.archives-ouvertes.fr/hal-01163019
  • 54K. Rafes, C. Germain.
    A platform for scientific data sharing, in: BDA2015 - Bases de Données Avancées, Île de Porquerolles, France, September 2015.
    https://hal.inria.fr/hal-01168496

Conferences without Proceedings

  • 55G. Grefenstette.
    InriaSAC: Simple Hypernym Extraction Methods, in: SemEval 2015, Denver, United States, June 2015.
    https://hal.inria.fr/hal-01112844
  • 56D. Rousseau, G. Cowan, C. A. Bourdarios, B. Kégl, C. Germain-Renaud, I. Guyon.
    The ATLAS Higgs Machine Learning Challenge, in: 21st International Conference on Computing in High Energy and Nuclear Physics – CHEP2015, Okinawa, Japan, April 2015, Proceedings to appear in Journal of Physics : Conference Series.
    http://hal.in2p3.fr/in2p3-01141742
  • 57P. Taillandier, P. Caillou, B. Gaudou, A. Grignard, B. Mathieu.
    Providing Modelers with a Simple Yet Rich Tool to Define Cognitive Agents with the GAMA Platform, in: Conference on Complex Systems (CCS 2015), Tempe, United States, September 2015.
    https://hal.inria.fr/hal-01216183

Scientific Books (or Scientific Book chapters)

  • 58NIPS 2014 Workshop on High-energy Physics and Machine Learning, JMLR Workshop and Conference Proceedings, June 2015, vol. 42, 134 p.
    https://hal.inria.fr/hal-01208543
  • 59A. Banos, P. Caillou, B. Gaudou, N. Marilleau.
    Agent-Based Model Exploration, in: Agent-Based Spatial Simulation with NetLogo, Volume 1: Introduction and Bases, Elsevier, September 2015, 57 p.
    https://hal.inria.fr/hal-01216192
  • 60A. Banos, P. Caillou, B. Gaudou, N. Marilleau.
    Exploration de modèles agent, in: Simulation spatiale à base d’agents avec NetLogo 1, ISTE, February 2015, 49 p.
    https://hal.inria.fr/hal-01216207
  • 61N. Hansen, D. V. Arnold, A. Auger.
    Evolution Strategies, in: Handbook of Computational Intelligence, J. Kacprzyk, W. Pedrycz (editors), 2015.
    https://hal.inria.fr/hal-01155533

Internal Reports

  • 62R. Akrour, B. Mayeur, M. Sebag.
    Direct Value Learning: Reinforcement Learning and Anti-Imitation, Inria ; CNRS ; Université Paris-Sud 11, December 2015, no RR-8836, 18 p.
    https://hal.inria.fr/hal-01249377
  • 63C. Furtlehner, A. Decelle.
    Cycle-based Cluster Variational Method for Direct and Inverse Inference, Inria Saclay, équipe TAO, October 2015, no RR-8788, 40 p.
    https://hal.inria.fr/hal-01214155

Other Publications


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