| 2025 | AAAI | OneBatchPAM: A Fast and Frugal K-Medoids Algorithm. | Antoine de Mathelin, Nicolas Enrique Cecchi, Franois Deheeger, Mathilde Mougeot, Nicolas Vayatis |
| 2025 | AISTATS | Collaborative non-parametric two-sample testing. | Alejandro D. de la Concha Duarte, Nicolas Vayatis, Argyris Kalogeratos |
| 2025 | AISTATS | Stein Boltzmann Sampling: A Variational Approach for Global Optimization. | Gatan Serr, Argyris Kalogeratos, Nicolas Vayatis |
| 2024 | AISTATS | Online non-parametric likelihood-ratio estimation by Pearson-divergence functional minimization. | Alejandro D. de la Concha Duarte, Nicolas Vayatis, Argyris Kalogeratos |
| 2023 | ICTAI | A Framework for Paired-Sample Hypothesis Testing for High-Dimensional Data. | Ioannis Bargiotas, Argyris Kalogeratos, Nicolas Vayatis |
| 2023 | ICTAI | Personalized One-Shot Collaborative Learning. | Marie Garin, Antoine de Mathelin, Mathilde Mougeot, Nicolas Vayatis |
| 2022 | ICLR | Discrepancy-Based Active Learning for Domain Adaptation. | Antoine de Mathelin, Franois Deheeger, Mathilde Mougeot, Nicolas Vayatis |
| 2021 | AISTATS | Offline detection of change-points in the mean for stationary graph signals. | Alejandro de la Concha, Nicolas Vayatis, Argyris Kalogeratos |
| 2021 | ICTAI | Adversarial Weighting for Domain Adaptation in Regression. | Antoine de Mathelin, Guillaume Richard, Franois Deheeger, Mathilde Mougeot, Nicolas Vayatis |
| 2020 | ICASSP | Low Rank Activations for Tensor-Based Convolutional Sparse Coding. | Pierre Humbert, Julien Audiffren, Laurent Oudre, Nicolas Vayatis |
| 2020 | ICML | Learning the piece-wise constant graph structure of a varying Ising model. | Batiste Le Bars, Pierre Humbert, Argyris Kalogeratos, Nicolas Vayatis |
| 2019 | ICASSP | Supervised Kernel Change Point Detection with Partial Annotations. | Charles Truong, Laurent Oudre, Nicolas Vayatis |
| 2019 | ICTAI | Optimal Multiple Stopping Rule for Warm-Starting Sequential Selection. | Mathilde Fekom, Nicolas Vayatis, Argyris Kalogeratos |
| 2018 | ICML | DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding. | Thomas Moreau, Laurent Oudre, Nicolas Vayatis |
| 2017 | ICML | Global optimization of Lipschitz functions. | Cdric Malherbe, Nicolas Vayatis |
| 2016 | ICML | A ranking approach to global optimization. | Cdric Malherbe, Emile Contal, Nicolas Vayatis |
| 2015 | ICTAI | A Greedy Approach for Dynamic Control of Diffusion Processes in Networks. | Kevin Scaman, Argyris Kalogeratos, Nicolas Vayatis |
| 2014 | ICML | Gaussian Process Optimization with Mutual Information. | Emile Contal, Vianney Perchet, Nicolas Vayatis |
| 2012 | ALT | Editors' Introduction. | Nader H. Bshouty, Gilles Stoltz, Nicolas Vayatis, Thomas Zeugmann |
| 2012 | ICML | Estimation of Simultaneously Sparse and Low Rank Matrices. | Pierre-Andr Savalle, Emile Richard, Nicolas Vayatis |
| 2009 | ALT | Adaptive Estimation of the Optimal ROC Curve and a Bipartite Ranking Algorithm. | Stphan Clmenon, Nicolas Vayatis |
| 2009 | ALT | Complexity versus Agreement for Many Views. | Odalric-Ambrym Maillard, Nicolas Vayatis |
| 2009 | ICML | Nonparametric estimation of the precision-recall curve. | Stphan Clmenon, Nicolas Vayatis |
| 2009 | ICMLA | Bagging Ranking Trees. | Stphan Clmenon, Marine Depecker, Nicolas Vayatis |
| 2008 | ALT | Approximation of the Optimal ROC Curve and a Tree-Based Ranking Algorithm. | Stphan Clmenon, Nicolas Vayatis |
| 2005 | COLT | Ranking and Scoring Using Empirical Risk Minimization. | Stphan Clmenon, Gbor Lugosi, Nicolas Vayatis |
| 2002 | COLT | A Consistent Strategy for Boosting Algorithms. | Gbor Lugosi, Nicolas Vayatis |
| 2000 | COLT | The Role of Critical Sets in Vapnik-Chervonenkis Theory. | Nicolas Vayatis |