Sébastien Gerchinovitz

According to our database1, Sébastien Gerchinovitz authored at least 27 papers between 2011 and 2024.

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Bibliography

2024
Diversity-Preserving K-Armed Bandits, Revisited.
Trans. Mach. Learn. Res., 2024

Certified Multifidelity Zeroth-Order Optimization.
SIAM/ASA J. Uncertain. Quantification, 2024

The Loss Landscape of Deep Linear Neural Networks: a Second-order Analysis.
J. Mach. Learn. Res., 2024

2023
Adaptive approximation of monotone functions.
CoRR, 2023

Certified Multi-Fidelity Zeroth-Order Optimization.
CoRR, 2023

2022
A general approximation lower bound in L<sup>p</sup> norm, with applications to feed-forward neural networks.
CoRR, 2022

Object Detection with Probabilistic Guarantees: A Conformal Prediction Approach.
Proceedings of the Computer Safety, Reliability, and Security. SAFECOMP 2022 Workshops, 2022

A general approximation lower bound in $L^p$ norm, with applications to feed-forward neural networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
White Paper Machine Learning in Certified Systems.
CoRR, 2021

Online nonparametric regression with Sobolev kernels.
CoRR, 2021

Numerical influence of ReLU'(0) on backpropagation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The Sample Complexity of Level Set Approximation.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Regret analysis of the Piyavskii-Shubert algorithm for global Lipschitz optimization.
CoRR, 2020

A High Probability Safety Guarantee for Shifted Neural Network Surrogates.
Proceedings of the Workshop on Artificial Intelligence Safety, 2020

2019
Uniform regret bounds over R<sup>d</sup> for the sequential linear regression problem with the square loss.
Proceedings of the Algorithmic Learning Theory, 2019

2018
Optimization of a SSP's Header Bidding Strategy using Thompson Sampling.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017
Fano's inequality for random variables.
CoRR, 2017

Online Nonparametric Learning, Chaining, and the Role of Partial Feedback.
CoRR, 2017

Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning.
Proceedings of the 30th Conference on Learning Theory, 2017

2016
Refined Lower Bounds for Adversarial Bandits.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Adaptive Simulated Annealing with Homogenization for Aircraft Trajectory Optimization.
Proceedings of the Operations Research Proceedings 2015, 2015

A Multiple-Play Bandit Algorithm Applied to Recommender Systems.
Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, 2015

A Chaining Algorithm for Online Nonparametric Regression.
Proceedings of The 28th Conference on Learning Theory, 2015

2014
Adaptive and optimal online linear regression on l<sup>1</sup>-balls.
Theor. Comput. Sci., 2014

2013
Sparsity regret bounds for individual sequences in online linear regression.
J. Mach. Learn. Res., 2013

2011
Adaptive and Optimal Online Linear Regression on ℓ1-Balls.
Proceedings of the Algorithmic Learning Theory - 22nd International Conference, 2011


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