Nicolas Vayatis
Orcid: 0000-0003-4308-4681
According to our database1,
Nicolas Vayatis
authored at least 101 papers
between 1999 and 2024.
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Bibliography
2024
2023
Online non-parametric likelihood-ratio estimation by Pearson-divergence functional minimization.
CoRR, 2023
Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification.
CoRR, 2023
Online Centralized Non-parametric Change-point Detection via Graph-based Likelihood-ratio Estimation.
CoRR, 2023
Proceedings of the 35th IEEE International Conference on Tools with Artificial Intelligence, 2023
Proceedings of the 35th IEEE International Conference on Tools with Artificial Intelligence, 2023
2022
IEEE Trans. Signal Process., 2022
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
J. Mach. Learn. Res., 2021
Image Process. Line, 2021
Online non-parametric change-point detection for heterogeneous data streams observed over graph nodes.
CoRR, 2021
Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021
Proceedings of the 29th European Signal Processing Conference, 2021
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
The Use of Inertial Measurement Units for the Study of Free Living Environment Activity Assessment: A Literature Review.
Sensors, 2020
SEAIR Framework Accounting for a Personalized Risk Prediction Score: Application to the Covid-19 Epidemic.
Image Process. Line, 2020
Tensor Convolutional Sparse Coding with Low-Rank activations, an application to EEG analysis.
CoRR, 2020
Multivariate two-sample hypothesis testing through AUC maximization for biomedical applications.
Proceedings of the SETN 2020: 11th Hellenic Conference on Artificial Intelligence, 2020
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
Proceedings of the 28th European Signal Processing Conference, 2020
2019
Image Process. Line, 2019
Local Assessment of Statokinesigram Dynamics in Time: An in-Depth Look at the Scoring Algorithm.
Image Process. Line, 2019
Selection of the Best Electroencephalogram Channel to Predict the Depth of Anesthesia.
Frontiers Comput. Neurosci., 2019
Revealing posturographic features associated with the risk of falling in patients with Parkinsonian syndromes via machine learning.
CoRR, 2019
Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019
Proceedings of the IEEE International Conference on Acoustics, 2019
Proceedings of the 27th European Signal Processing Conference, 2019
Proceedings of the 58th IEEE Conference on Decision and Control, 2019
2018
Proceedings of the 35th International Conference on Machine Learning, 2018
The Complementary Role of Activity Context in the Mental Workload Evaluation of Helicopter Pilots: A Multi-tasking Learning Approach.
Proceedings of the Human Mental Workload: Models and Applications, 2018
2017
CoRR, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the 25th European Signal Processing Conference, 2017
Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017
2016
IEEE Trans. Netw. Sci. Eng., 2016
Quantitative Analysis of Dynamic Fault Trees Based on the Coupling of Structure Functions and Monte Carlo Simulation.
Qual. Reliab. Eng. Int., 2016
CoRR, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
2015
Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence, 2015
2014
What Makes a Good Plan? An Efficient Planning Approach to Control Diffusion Processes in Networks.
CoRR, 2014
Nonparametric Markovian Learning of Triggering Kernels for Mutually Exciting and Mutually Inhibiting Multivariate Hawkes Processes.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014
Tight Bounds for Influence in Diffusion Networks and Application to Bond Percolation and Epidemiology.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
Proceedings of the 31th International Conference on Machine Learning, 2014
Proceedings of the Complex Systems Design & Management, 2014
2013
An empirical comparison of learning algorithms for nonparametric scoring: the TreeRank algorithm and other methods.
Pattern Anal. Appl., 2013
Mach. Learn., 2013
Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013
2012
A Regularization Approach for Prediction of Edges and Node Features in Dynamic Graphs
CoRR, 2012
Proceedings of the 29th International Conference on Machine Learning, 2012
Proceedings of the Algorithmic Learning Theory - 23rd International Conference, 2012
2011
Rev. d'Intelligence Artif., 2011
Adaptive partitioning schemes for bipartite ranking - How to grow and prune a ranking tree.
Mach. Learn., 2011
2010
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010
2009
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
Proceedings of the International Conference on Machine Learning and Applications, 2009
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
Proceedings of the Algorithmic Learning Theory, 20th International Conference, 2009
Proceedings of the Algorithmic Learning Theory, 20th International Conference, 2009
2008
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
Proceedings of the Algorithmic Learning Theory, 19th International Conference, 2008
2007
2006
Remark on "Recursive Aggregation of Estimators by the Mirror Descent Algorithm with Averaging" published in <i>Probl. Peredachi Inf.</i>, 2005, no. 4.
Probl. Inf. Transm., 2006
2005
Probl. Inf. Transm., 2005
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005
Proceedings of the From Data and Information Analysis to Knowledge Engineering, 2005
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005
2003
J. Mach. Learn. Res., 2003
2002
Proceedings of the Computational Learning Theory, 2002
2000
The Role of Critical Sets in Vapnik-Chervonenkis Theory.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000
1999
Proceedings of the Computational Learning Theory, 4th European Conference, 1999