Moïse Blanchard

According to our database, Moïse Blanchard authored at least 20 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Probabilistic Bounds on the <i>k</i>-Traveling Salesman Problem and the Traveling Repairman Problem.

Moïse Blanchard, Alexandre Jacquillat, Patrick Jaillet

Math. Oper. Res., 2024

Agnostic Smoothed Online Learning.

Moïse Blanchard

CoRR, 2024

Near-Optimal Mechanisms for Resource Allocation Without Monetary Transfers.

Moïse Blanchard, Patrick Jaillet

CoRR, 2024

Gradient Descent is Pareto-Optimal in the Oracle Complexity and Memory Tradeoff for Feasibility Problems.

Moïse Blanchard

Proceedings of the 65th IEEE Annual Symposium on Foundations of Computer Science, 2024

Correlated Binomial Process.

Moïse Blanchard, Doron Cohen, Aryeh Kontorovich

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Tight Bounds for Local Glivenko-Cantelli.

Moïse Blanchard, Václav Vorácek

Proceedings of the International Conference on Algorithmic Learning Theory, 2024

2023

Memory-Constrained Algorithms for Convex Optimization via Recursive Cutting-Planes.

Moïse Blanchard, Junhui Zhang, Patrick Jaillet

CoRR, 2023

Non-stationary Contextual Bandits and Universal Learning.

Moïse Blanchard, Steve Hanneke, Patrick Jaillet

CoRR, 2023

Contextual Bandits and Optimistically Universal Learning.

Moïse Blanchard, Steve Hanneke, Patrick Jaillet

CoRR, 2023

Memory-Constrained Algorithms for Convex Optimization.

Moïse Blanchard, Junhui Zhang, Patrick Jaillet

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Quadratic Memory is Necessary for Optimal Query Complexity in Convex Optimization: Center-of-Mass is Pareto-Optimal.

Moïse Blanchard, Junhui Zhang, Patrick Jaillet

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Additional Results and Extensions for the paper "Probabilistic bounds on the k-Traveling Salesman Problem and the Traveling Repairman Problem".

Moïse Blanchard, Alexandre Jacquillat, Patrick Jaillet

CoRR, 2022

Probabilistic bounds on the k-Traveling Salesman Problem and the Traveling Repairman Problem.

Moïse Blanchard, Alexandre Jacquillat, Patrick Jaillet

CoRR, 2022

Universal Regression with Adversarial Responses.

Moïse Blanchard, Patrick Jaillet

CoRR, 2022

Shallow and Deep Networks are Near-Optimal Approximators of Korobov Functions.

Moïse Blanchard, Mohammed Amine Bennouna

Proceedings of the Tenth International Conference on Learning Representations, 2022

Universal Online Learning with Bounded Loss: Reduction to Binary Classification.

Moïse Blanchard, Romain Cosson

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Universal Online Learning: an Optimistically Universal Learning Rule.

Moïse Blanchard

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Universal Online Learning with Unbounded Losses: Memory Is All You Need.

Moïse Blanchard, Romain Cosson, Steve Hanneke

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

2021

On the Length of Monotone Paths in Polyhedra.

Moïse Blanchard, Jesús A. De Loera, Quentin Louveaux

SIAM J. Discret. Math., 2021

2020

The Representation Power of Neural Networks: Breaking the Curse of Dimensionality.

Moïse Blanchard, M. Amine Bennouna

CoRR, 2020