Publications

2016

Rémi Lemonnier, Kevin. Scaman, Argyris Kalogeratos.
Multivariate Hawkes Processes for Large-scale Inference.
Proceedings of 2017 AAAI Conference on Artificial Intelligence, San Francisco, CA, US.

Kevin Scaman, Argyris Kalogeratos, Nicolas Vayatis.
Suppressing Epidemics in Networks using Priority-Planning.
IEEE Transactions on Network Science and Engineering, 2017.

Argyris Kalogeratos, P. Zagorisios, A. Likas.
Improving Text Stream Clustering using Term Burstiness and Co-burstiness, A. Hellenic Conference of Artificial Intelligence (SETN), 2016.

2015

Kevin Scaman, Rémi Lemonnier, Nicolas Vayatis.
Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks.
Proceedings of NIPS 2015.

Julien Audiffren, Liva Ralaivola.
Cornering Stationary and Restless Mixing Bandits with Remix-UCB.
Proceedings of NIPS 2015.

Argyris Kalogeratos, Kevin Scaman, Nicolas Vayatis.
Learning to Suppress SIS Epidemics in Networks.
NIPS 2015 Networks in the Social and Information Sciences workshop, 2015.

Kevin Scaman, Argyris Kalogeratos, and Nicolas Vayatis.
A Greedy Approach for Dynamic Control of Diffusion Processes in Networks.
Proceedings of the IEEE International Conference on Tools with Artificial Intelligence (ICTAI), November 9-12, 2015/

Suzanne Varet, Pierre Dossantos-Uzarralde, Nicolas Vayatis.
Quality quantification of evaluated cross section covariances.
Nuclear Data Sheets 123, p.191-195, (2015).

Suzanne Varet, Pierre Dossantos-Uzarralde, Nicolas Vayatis.
A statistical approach for experimental crosssection covariances estimation via shrinkage.
Nuclear Science and Engineering 179(4), p.398-410 (2015).

Thomas Moreau , Laurent Oudre , Nicolas Vayatis.
Groupement automatique pour l’analyse du spectre singulier.
Colloque du GRETSI.

Charles Truong , Laurent Oudre , Nicolas Vayatis.
Segmentation de signaux physiologiques par optimisation globale.
Colloque du GRETSI.

2014

Themistoklis S. Stefanakis, Emile Contal, Nicolas Vayatis, Frédéric Dias, and Costas E. Synolakis.
Can Small Islands Protect Nearby Coasts From Tsunamis? An Active Experimental Design Approach .
Proceedings of the Royal Society-A. Accepted. [arXiv:1305.7385.]

Kevin Scaman, Argyris Kalogeratos, Nicolas Vayatis.
What Makes a Good Plan? An Efficient Planning Approach to Control Diffusion Processes in Networks.
arXiv:1407.4760, 17 Jul 2014

Rémi Lemonnier, Kevin Scaman, Nicolas Vayatis.
Tight Bounds for Influence in Diffusion Networks and Application to Bond Percolation and Epidemiology.
Proceedings of NIPS’14

Rémi Lemonnier, Nicolas Vayatis.
Nonparametric Markovian Learning of Triggering Kernels for Mutually Exciting and Mutually Inhibiting Multivariate Hawkes Processes.
Proceedings of ECML’14

Emile Contal, Vianney Perchet, Nicolas Vayatis.
Gaussian Process Optimization with Mutual Information.
Proceedings of ICML’14 and JMLR W&CP 32 (1) : 253–261

Joris Costes, Jean-Michel Ghidaglia, Philippe Muguerra, Keld Lund Nielsen, Xavier Riou, Jean-Philippe Saut and Nicolas Vayatis.
On the Simulation of Offshore Oil Facilities at the System Level.
Proceedings of the 10th International Modelica Conference

K. Scaman, A. Kalogeratos, N. Vayatis.
Dynamic Treatment Allocation for Epidemic Control in Arbitrary Networks.
Proceedings of WSDM 2014 Diffusion in Networks and Cascade Analytics (DiffNet) Workshop, February, NYC.

E. Richard, S. Gaiffas, and N. Vayatis.
Link Prediction in Graphs with Autoregressive Features.
Journal of Machine Learning Research. Volume 15(Feb):565−593.

S. Varet, P. Dossantos-Uzarralde, N. Vayatis and E. Bauge.
A method using Pseudo-measurements and shrinkage for the estimation of cross section covariances.
Nuclear Data Sheets, 118, p.357-359.

S. Varet, P. Dossantos-Uzarralde, N. Vayatis.
A statistical approach for experimental cross-section covariances estimation via shrinkage.
Nuclear Science and Engineering, Accepted.

S. Varet, P. Dossantos-Uzarralde, N. Vayatis.
Quality quantification of evaluated cross section covariances.
Proceedings of the CW2014 workshop.

S. Varet, P. Dossantos-Uzarralde, N. Vayatis.
Uncertainty estimation of nuclear interaction description from a model hierarchy.
Proceedings of the Uncertainties 2014 Conference.

G. Merle, J.-M. Roussel, V. Perchet, J.-J. Lesage and N. Vayatis.
Quantitative analysis of Dynamic Fault Trees based on the coupling of structure functions ure functions and Monte-Carlo simulation.
Quality and Reliability Engineering International. Accepted.

A. Kohatsu-Higa, N. Vayatis, and K. Yasuda
Strong Consistency of the Bayesian Estimator for the Ornstein–Uhlenbeck Process.
Book Chapter in Y. Kabanov, M. Rutkowski, T. Zariphopoulou (eds.), Inspired by Finance – The Musiela Festschrift: 411-437.
Nicolas Vayatis
Applications of concentration inequalities for statistical scoring and ranking problems
ESAIM: PROCEEDINGS, January 2014, Vol. 44, p. 99-109.

2013

S. Clémençon, M. Depecker, and N. Vayatis.
Ranking Forests.
Journal of Machine Learning Research. Volume 14(Jan):39-73.

S. Clémençon, S. Robbiano, and N. Vayatis.
Ranking data with ordinal labels: optimality and pairwise aggregation.
Machine Learning.  Volume 91(1): 67-104.

E. Richard, A. Argyriou, T. Evgeniou, N. Vayatis.
A Regularization Approach for Prediction of Edges and Node Features in Dynamic Graphs.
arXiv:1203.5438

Emile Contal, David Buffoni, Alexandre Robicquet, and N. Vayatis.
Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration.
Proceedings of European Conference on Machine Learning, Prague.

F. Dias, S. Guillas, N. Vayatis, A. Sarri, T. S. Stefanakis, E. Contal and C. E. Synolakis .
New methods for sensitivity analysis and uncertainty quantification of tsunamis.
Proceedings of the 14th Asia Congress of Fluid Mechanics, Hanoi and Halong, Vietnam.

S. Varet, P. Dossantos-Uzarralde, N. Vayatis,  E. Bauge
Pseudo-measurement simulations and shrinkage for the experimental cross-section covariances optimisation .
Proceedings of the International Conference on Nuclear Data for Science and Technology,  NYC.

P. Dossantos-Uzarralde,  N. Vayatis, S. Varet
Statistical selection of numerical models with deterministic parameters for cross-section uncertainty evaluations .
Proceedings of the International Conference on Nuclear Data for Science and Technology, NYC.

A. Dematteo, S. Clémençon, N. Vayatis, M. Mougeot.
Sloshing in the LNG shipping industry: risk modelling through multivariate heavy-tail analysis.
arXiv:1312.0020

S. Clémençon, M. Depecker, and N. Vayatis.
An empirical comparison of learning algorithms for nonparametric scoring. The TreeRank algorithm and other methods.
Pattern Analysis and Applications.  Vol. 16: 475-496, 2013.

2012

E. Richard, P.A. Savalle, and N. Vayatis.
Estimating simultaneously sparse and low-rank matrices.
Proceedings of ICML’12.

E. Richard, S. Gaiffas, and N. Vayatis.
Link Prediction in Graphs with Autoregressive Features.
Proceedings of NIPS’12.

E. Richard,D. Buffoni, N. Baskiotis, and N. Vayatis.
Taking the best of many link recommendations and applications to C2C e-commerce.
Preprint.

T.S. Stefanakis, F. Dias, N. Vayatis, and S. Guillas.
Long-Wave Runup On A Plane Beach Behind A Conical Island.
Proceedings of 15 WCEE, Lisboa.

S. Varet, P. Dossantos-Uzarralde, N. Vayatis, and E. Bauge.
Pseudo-measurement simulations and bootstrap for the experimental cross-section covariances estimation with quality qualification.
Wonder 2012: 3rd International Workshop on Nuclear Data Evaluation for Reactor Applications (Aix-en-Provence).

S. Varet, A. Garlaud, P. Dossantos-Uzarralde, N. Vayatis, and E. Bauge.
Kriging approach for the experimental cross-section covariances estimation.
Wonder 2012: 3rd International Workshop on Nuclear Data Evaluation for Reactor Applications (Aix-en-Provence).

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