Search Machine Learning Repository:
All publications by Nicolas Vayatis
authors venues years



Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks
Kevin Scaman, Rémi Lemonnier and Nicolas Vayatis
Advances in Neural Information Processing Systems 28, 2015


Gaussian Process Optimization with Mutual Information
Emile Contal, Vianney Perchet and Nicolas Vayatis
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Tight Bounds for Influence in Diffusion Networks and Application to Bond Percolation and Epidemiology
Remi Lemonnier, Kevin Scaman and Nicolas Vayatis
Advances in Neural Information Processing Systems 27, 2014


Link Prediction in Graphs with Autoregressive Features
Emile Richard, Stephane Gaiffas and Nicolas Vayatis
Advances in Neural Information Processing Systems 25, 2012


Estimation of Simultaneously Sparse and Low Rank Matrices
Emile Richard, Pierre-andre Savalle and Nicolas Vayatis
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Link Discovery using Graph Feature Tracking
Emile Richard, Nicolas Baskiotis, Theodoros Evgeniou and Nicolas Vayatis
Advances in Neural Information Processing Systems 23, 2010


Nonparametric estimation of the precision-recall curve
Nicolas Vayatis and Stéphan J. Clémençcon
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


AUC optimization and the two-sample problem
Nicolas Vayatis, Marine Depecker and Stéphan J. Clémençcon
Advances in Neural Information Processing Systems 22, 2009


On Partitioning Rules for Bipartite Ranking
Stéphan Clémençcon and Nicolas Vayatis
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


On Bootstrapping the ROC Curve
Patrice Bertail, Stéphan J. Clémençcon and Nicolas Vayatis
Advances in Neural Information Processing Systems 21, 2008


Overlaying classifiers: a practical approach for optimal ranking
Stéphan J. Clémençcon and Nicolas Vayatis
Advances in Neural Information Processing Systems 21, 2008


Empirical performance maximization for linear rank statistics
Stéphan J. Clémençcon and Nicolas Vayatis
Advances in Neural Information Processing Systems 21, 2008


Ranking the Best Instances
Stéphan Clémençcon and Nicolas Vayatis
Journal of Machine Learning Research, 2007


Generalization Error Bounds for Aggregation by Mirror Descent with Averaging
Anatoli Juditsky, Alexander Nazin, Alexandre Tsybakov and Nicolas Vayatis
Advances in Neural Information Processing Systems 18, 2005


On the Rate of Convergence of Regularized Boosting Classifiers
Gilles Blanchard, Gábor Lugosi and Nicolas Vayatis
Journal of Machine Learning Research, 2003