Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

• 1C. Keribin.
  From clustering to co-clustering : a model based approach, Université Paris Sud XI, November 2019, Habilitation à diriger des recherches.
  https://tel.archives-ouvertes.fr/tel-02397429

Articles in International Peer-Reviewed Journals

• 2S. Arlot.
  Minimal penalties and the slope heuristics: a survey, in: Journal de la Société Française de Statistique, October 2019, vol. 160, n^o 3, pp. 1-106, https://arxiv.org/abs/1901.07277.
  https://hal.archives-ouvertes.fr/hal-01989167
• 3S. Arlot.
  Rejoinder on: Minimal penalties and the slope heuristics: a survey, in: Journal de la Société Française de Statistique, October 2019, vol. 160, n^o 3, pp. 158-168, https://arxiv.org/abs/1909.13499.
  https://hal.archives-ouvertes.fr/hal-02300688
• 4S. Arlot, A. Celisse, Z. Harchaoui.
  A Kernel Multiple Change-point Algorithm via Model Selection, in: Journal of Machine Learning Research, December 2019, vol. 20, n^o 162, pp. 1–56, https://arxiv.org/abs/1202.3878.
  https://hal.archives-ouvertes.fr/hal-00671174
• 5M. Brégère, P. Gaillard, Y. Goude, G. Stoltz.
  Target Tracking for Contextual Bandits: Application to Demand Side Management, in: Proceedings of Machine Learning Research, June 2019, vol. 97, pp. 754-763, https://arxiv.org/abs/1901.09532.
  https://hal.archives-ouvertes.fr/hal-01994144
• 6G. Chinot, G. Lecué, M. Lerasle.
  Robust Statistical learning with Lipschitz and convex loss functions, in: Probability Theory and Related Fields, July 2019, https://arxiv.org/abs/1810.01090. [ DOI : 10.1007_s00440-019-00931-3 ]
  https://hal.archives-ouvertes.fr/hal-01923033
• 7A. Havet, M. Lerasle, É. Moulines.
  Density estimation for RWRE, in: Mathematical Methods of Statistics, March 2019, https://arxiv.org/abs/1806.05839. [ DOI : 10.3103/S1066530719010022 ]
  https://hal.archives-ouvertes.fr/hal-01815990
• 8C. Keribin.
  A note on BIC and the slope heuristic, in: Journal de la Société Française de Statistique, 2019.
  https://hal.archives-ouvertes.fr/hal-02391310
• 9C. Keribin, Y. Liu, T. Popova, Y. Rozenholc.
  A mixture model to characterize genomic alterations of tumors, in: Journal de la Société Française de Statistique, 2019.
  https://hal.archives-ouvertes.fr/hal-02391289
• 10G. Lecué, M. Lerasle.
  Robust machine learning by median-of-means : theory and practice, in: Annals of Statistics, February 2019, https://arxiv.org/abs/1711.10306 - 48 pages, 6 figures.
  https://hal.archives-ouvertes.fr/hal-01923036

Invited Conferences

• 11C. Biernacki, G. Celeux, J. Josse, F. Laporte.
  Dealing with missing data in model-based clustering through a MNAR model, in: CRoNos & MDA 2019 - Meeting and Workshop on Multivariate Data Analysis and Software, Limassol, Cyprus, April 2019.
  https://hal.inria.fr/hal-02103347

International Conferences with Proceedings

• 12M. Lerasle, Z. Szabó, T. Mathieu, G. Lecué.
  MONK – Outlier-Robust Mean Embedding Estimation by Median-of-Means, in: ICML 2019 - 36th International Conference on Machine Learning, Long Beach, United States, Proceedings of Machine Learning Research, June 2019.
  https://hal.archives-ouvertes.fr/hal-01705881

Conferences without Proceedings

• 13E. Chzhen, C. Denis, M. Hebiri, L. Oneto, M. Pontil.
  Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification, in: NeurIPS, Vancouver, Canada, December 2019, https://arxiv.org/abs/1906.05082.
  https://hal-upec-upem.archives-ouvertes.fr/hal-02150662
• 14H. Hadiji.
  Polynomial Cost of Adaptation for X -Armed Bandits, in: Thirty-third Conference on Neural Information Processing Systems, Vancouver, France, December 2019, https://arxiv.org/abs/1905.10221.
  https://hal.archives-ouvertes.fr/hal-02138492
• 15C. Keribin, C. Biernacki.
  Co-clustering: model based or model free approaches, in: 62nd ISI World Statistics Congress 2019, Kuala Lumpur, Malaysia, August 2019.
  https://hal.archives-ouvertes.fr/hal-02399031
• 16C. Keribin, C. Biernacki.
  Le modèle des blocs latents, une méthode régularisée pour la classification en grande dimension, in: JdS 2019 - 51èmes Journées de Statistique de la SFdS, Nancy, France, June 2019.
  https://hal.archives-ouvertes.fr/hal-02391379
• 17C. Keribin.
  Some Asymptotic Properties of Model Selection Criteria in the Matent Block Model, in: CLADAG 2019 - 12th Scientific Meeting Classification and Data Analysis Group, Cassino, Italy, September 2019.
  https://hal.archives-ouvertes.fr/hal-02391398
• 18F. Laporte, C. Biernacki, G. Celeux, J. Josse.
  Modèles de classification non supervisée avec données manquantes non au hasard, in: 51e journées de statistique, Nancy, France, June 2019.
  https://hal.archives-ouvertes.fr/hal-02398984

Other Publications

• 19G. Celeux, P. Pamphile.
  Estimating parameters of the Weibull Competing Risk model with Masked Causes and Heavily Censored Data, December 2019, working paper or preprint.
  https://hal.inria.fr/hal-02410489
• 20G. Chinot, G. Lecué, M. Lerasle.
  Robust high dimensional learning for Lipschitz and convex losses, June 2019, https://arxiv.org/abs/1905.04281 - working paper or preprint.
  https://hal.archives-ouvertes.fr/hal-02159943
• 21F. Ducros, P. Pamphile.
  Maintenance cost forecasting for a fleet of vehicles, February 2019, working paper or preprint.
  https://hal.archives-ouvertes.fr/hal-02055175
• 22A. Garivier, H. Hadiji, P. Menard, G. Stoltz.
  KL-UCB-switch: optimal regret bounds for stochastic bandits from both a distribution-dependent and a distribution-free viewpoints, November 2019, working paper or preprint.
  https://hal.archives-ouvertes.fr/hal-01785705
• 23C. Giraud, Y. Issartel, L. Lehéricy, M. Lerasle.
  Pair Matching: When bandits meet stochastic block model, June 2019, https://arxiv.org/abs/1905.07342 - 57 pages.
  https://hal.archives-ouvertes.fr/hal-02159938
• 24A. Havet, M. Lerasle, É. Moulines, E. Vernet.
  A quantitative Mc Diarmid's inequality for geometrically ergodic Markov chains, July 2019, https://arxiv.org/abs/1907.02809 - working paper or preprint.
  https://hal.archives-ouvertes.fr/hal-02177452
• 25Y. Issartel.
  On the Estimation of Network Complexity: Dimension of Graphons, December 2019, https://arxiv.org/abs/1909.02900 - working paper or preprint.
  https://hal.archives-ouvertes.fr/hal-02413537
• 26A. Janon.
  Global optimization using Sobol indices, June 2019, working paper or preprint.
  https://hal.archives-ouvertes.fr/hal-02154121
• 27F. Laporte, C. Biernacki, G. Celeux, J. Josse.
  Model-based clustering with missing not at random data. Missing mechanism, July 2019, Working Group on Model-Based Clustering Summer Session, Poster.
  https://hal.archives-ouvertes.fr/hal-02398987
• 28G. Maillard, S. Arlot, M. Lerasle.
  Aggregated Hold-Out, September 2019, https://arxiv.org/abs/1909.04890 - working paper or preprint.
  https://hal.archives-ouvertes.fr/hal-02273193
• 29S. Minsker, T. Mathieu.
  Excess risk bounds in robust empirical risk minimization, December 2019, https://arxiv.org/abs/1910.07485 - working paper or preprint. [ DOI : 10.07485 ]
  https://hal.archives-ouvertes.fr/hal-02390397
• 30V. Robert, Y. Vasseur, V. Brault.
  Comparing high dimensional partitions with the Coclustering Adjusted Rand Index, January 2019, working paper or preprint.
  https://hal.inria.fr/hal-01524832