Alex Ayoub

Orcid: 0009-0004-7034-1721

According to our database1, Alex Ayoub authored at least 14 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Efficient Simple Regret Algorithms for Stochastic Contextual Bandits.
CoRR, January, 2026

Eluder dimension: localise it!
CoRR, January, 2026

2025
Learning to Reason Efficiently with Discounted Reinforcement Learning.
CoRR, October, 2025

Rectifying Regression in Reinforcement Learning.
CoRR, October, 2025

Does Weighting Improve Matrix Factorization for Recommender Systems?
Proceedings of the ACM on Web Conference 2025, 2025

2024
Mitigating the Curse of Horizon in Monte-Carlo Returns.
RLJ, 2024

Almost Free: Self-concordance in Natural Exponential Families and an Application to Bandits.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Switching the Loss Reduces the Cost in Batch Reinforcement Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Exploration via linearly perturbed loss minimisation.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Resmax: An Alternative Soft-Greedy Operator for Reinforcement Learning.
Trans. Mach. Learn. Res., 2023

Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021
An Elementary Proof that Q-learning Converges Almost Surely.
CoRR, 2021

Randomized Exploration in Reinforcement Learning with General Value Function Approximation.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Model-Based Reinforcement Learning with Value-Targeted Regression.
Proceedings of the 37th International Conference on Machine Learning, 2020


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