Moïse Blanchard

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 21

Top Topics

Traveling Salesman

Convex Optimization

Pareto Optimality

Top Venues

Math. Oper. Res.

Publications

Moïse Blanchard
Gradient Descent is Pareto-Optimal in the Oracle Complexity and Memory Tradeoff for Feasibility Problems. CoRR (2024)
Moïse Blanchard, Doron Cohen, Aryeh Kontorovich
Correlated Binomial Process. COLT (2024)
Moïse Blanchard, Alexandre Jacquillat, Patrick Jaillet
-Traveling Salesman Problem and the Traveling Repairman Problem. Math. Oper. Res. 49 (2) (2024)
Moïse Blanchard, Václav Vorácek
Tight Bounds for Local Glivenko-Cantelli. ALT (2024)
Moïse Blanchard, Steve Hanneke, Patrick Jaillet
Contextual Bandits and Optimistically Universal Learning. CoRR (2023)
Moïse Blanchard, Junhui Zhang, Patrick Jaillet
Quadratic Memory is Necessary for Optimal Query Complexity in Convex Optimization: Center-of-Mass is Pareto-Optimal. CoRR (2023)
Moïse Blanchard, Junhui Zhang, Patrick Jaillet
Memory-Constrained Algorithms for Convex Optimization. NeurIPS (2023)
Moïse Blanchard, Junhui Zhang, Patrick Jaillet
Quadratic Memory is Necessary for Optimal Query Complexity in Convex Optimization: Center-of-Mass is Pareto-Optimal. COLT (2023)
Moïse Blanchard, Steve Hanneke, Patrick Jaillet
Non-stationary Contextual Bandits and Universal Learning. CoRR (2023)
Moïse Blanchard, Junhui Zhang, Patrick Jaillet
Memory-Constrained Algorithms for Convex Optimization via Recursive Cutting-Planes. CoRR (2023)
Moïse Blanchard, Patrick Jaillet
Universal Regression with Adversarial Responses. CoRR (2022)
Moïse Blanchard, Romain Cosson
Universal Online Learning with Bounded Loss: Reduction to Binary Classification. COLT (2022)
Moïse Blanchard, Alexandre Jacquillat, Patrick Jaillet
Probabilistic bounds on the k-Traveling Salesman Problem and the Traveling Repairman Problem. CoRR (2022)
Moïse Blanchard
Universal Online Learning: an Optimistically Universal Learning Rule. CoRR (2022)
Moïse Blanchard
Universal Online Learning: an Optimistically Universal Learning Rule. COLT (2022)
Moïse Blanchard, Romain Cosson, Steve Hanneke
Universal Online Learning with Unbounded Losses: Memory Is All You Need. ALT (2022)
Moïse Blanchard, Mohammed Amine Bennouna
Shallow and Deep Networks are Near-Optimal Approximators of Korobov Functions. ICLR (2022)
Moïse Blanchard, Alexandre Jacquillat, Patrick Jaillet
Additional Results and Extensions for the paper "Probabilistic bounds on the k-Traveling Salesman Problem and the Traveling Repairman Problem". CoRR (2022)
Moïse Blanchard, Romain Cosson, Steve Hanneke
Universal Online Learning with Unbounded Losses: Memory Is All You Need. CoRR (2022)
Moïse Blanchard, Jesús A. De Loera, Quentin Louveaux
On the Length of Monotone Paths in Polyhedra. SIAM J. Discret. Math. 35 (3) (2021)
Moïse Blanchard, Romain Cosson
Universal Online Learning with Bounded Loss: Reduction to Binary Classification. CoRR (2021)