A ranking approach to global optimization

Cédric Malherbe, Nicolas Vayatis

A Spectral Method for Activity Shaping in Continuous-Time Information Cascades

Kevin Scaman, Argyris Kalogeratos, Luca Corinzia +1

Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration

Emile Contal, David Buffoni, Alexandre Robicquet +1

Optimization for Gaussian Processes via Chaining

Emile Contal, Cédric Malherbe, Nicolas Vayatis

Nonparametric Markovian Learning of Triggering Kernels for Mutually Exciting and Mutually Inhibiting Multivariate Hawkes Processes

Remi Lemonnier, Nicolas Vayatis

Link Prediction in Graphs with Autoregressive Features

Emile Richard, Stephane Gaiffas, Nicolas Vayatis

DICOD: Distributed Convolutional Sparse Coding

Thomas Moreau, Laurent Oudre, Nicolas Vayatis

A Regularization Approach for Prediction of Edges and Node Features in Dynamic Graphs

Emile Richard, Andreas Argyriou, Theodoros Evgeniou +1

Revealing posturographic features associated with the risk of falling in patients with Parkinsonian syndromes via machine learning

Ioannis Bargiotas, Argyris Kalogeratos, Myrto Limnios +3

ruptures: change point detection in Python

Charles Truong, Laurent Oudre, Nicolas Vayatis

Can Small Islands Protect Nearby Coasts From Tsunamis? An Active Experimental Design Approach

Themistoklis S. Stefanakis, Emile Contal, Nicolas Vayatis +2

Discussion of ``2004 IMS Medallion Lecture: Local Rademacher complexities and oracle inequalities in risk minimization'' by V. Koltchinskii

Stéphan Clémençon, Gábor Lugosi, Nicolas Vayatis

Recursive Aggregation of Estimators by Mirror Descent Algorithm with Averaging

Anatoli Juditsky, Alexander Nazin, Alexandre Tsybakov +1

Ranking the best instances

Stéphan Clémençon, Nicolas Vayatis

Tight Bounds for Influence in Diffusion Networks and Application to Bond Percolation and Epidemiology

Remi Lemonnier, Kevin Scaman, Nicolas Vayatis

Spectral Bounds in Random Graphs Applied to Spreading Phenomena and Percolation

Rémi Lemonnier, Kevin Scaman, Nicolas Vayatis

Graph Prediction in a Low-Rank and Autoregressive Setting

Emile Richard, Pierre-Andre Savalle, Nicolas Vayatis

Gaussian Process Optimization with Mutual Information

Emile Contal, Vianney Perchet, Nicolas Vayatis

Ranking and empirical minimization of U-statistics

Stéphan Clémençon, Gábor Lugosi, Nicolas Vayatis

What Makes a Good Plan? An Efficient Planning Approach to Control Diffusion Processes in Networks

Kevin Scaman, Argyris Kalogeratos, Nicolas Vayatis

Multivariate Convolutional Sparse Coding with Low Rank Tensor

Pierre Humbert, Julien Audiffren, Laurent Oudre +1

The paper proposes a multivariate convolutional sparse coding method that uses tensor algebra and CP decomposition to enforce element-wise sparsity and low-rank structure in activa…

Global optimization of Lipschitz functions

Cédric Malherbe, Nicolas Vayatis

Sloshing in the LNG shipping industry: risk modelling through multivariate heavy-tail analysis

Antoine Dematteo, Stéphan CLEMENCON, Nicolas Vayatis +1

Stochastic Process Bandits: Upper Confidence Bounds Algorithms via Generic Chaining

Emile Contal, Nicolas Vayatis