Team, Visitors, External Collaborators
Overall Objectives
Research Program
Application Domains
New Software and Platforms
New Results
Partnerships and Cooperations
Dissemination
Bibliography
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Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

[1]
C. 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

[2]
S. Arlot.
Minimal penalties and the slope heuristics: a survey, in: Journal de la Société Française de Statistique, October 2019, vol. 160, no 3, pp. 1-106, https://arxiv.org/abs/1901.07277.
https://hal.archives-ouvertes.fr/hal-01989167
[3]
S. Arlot.
Rejoinder on: Minimal penalties and the slope heuristics: a survey, in: Journal de la Société Française de Statistique, October 2019, vol. 160, no 3, pp. 158-168, https://arxiv.org/abs/1909.13499.
https://hal.archives-ouvertes.fr/hal-02300688
[4]
S. Arlot, A. Celisse, Z. Harchaoui.
A Kernel Multiple Change-point Algorithm via Model Selection, in: Journal of Machine Learning Research, December 2019, vol. 20, no 162, pp. 1–56, https://arxiv.org/abs/1202.3878.
https://hal.archives-ouvertes.fr/hal-00671174
[5]
M. 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
[6]
G. 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
[7]
A. 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
[8]
C. 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
[9]
C. 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
[10]
G. 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

[11]
C. 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

[12]
M. 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

[13]
E. 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
[14]
H. 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
[15]
C. 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
[16]
C. 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
[17]
C. 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
[18]
F. 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

[19]
G. 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
[20]
G. 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
[21]
F. Ducros, P. Pamphile.
Maintenance cost forecasting for a fleet of vehicles, February 2019, working paper or preprint.
https://hal.archives-ouvertes.fr/hal-02055175
[22]
A. 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
[23]
C. 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
[24]
A. 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
[25]
Y. 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
[26]
A. Janon.
Global optimization using Sobol indices, June 2019, working paper or preprint.
https://hal.archives-ouvertes.fr/hal-02154121
[27]
F. 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
[28]
G. 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
[29]
S. 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
[30]
V. 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