Zakaria Mhammedi

According to our database, Zakaria Mhammedi authored at least 30 papers between 2017 and 2025.

Collaborative distances:

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

2025

Sample and Oracle Efficient Reinforcement Learning for MDPs with Linearly-Realizable Value Functions.

Zakaria Mhammedi

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

Online Convex Optimization with a Separation Oracle.

Zakaria Mhammedi

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

Is a Good Foundation Necessary for Efficient Reinforcement Learning? The Computational Role of the Base Model in Exploration.

Dylan J. Foster, Zakaria Mhammedi, Dhruv Rohatgi

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

2024

Improved Sample Complexity of Imitation Learning for Barrier Model Predictive Control.

Daniel Pfrommer, Swati Padmanabhan, Kwangjun Ahn, Jack Umenberger, Tobia Marcucci, Zakaria Mhammedi, Ali Jadbabaie

CoRR, 2024

The Power of Resets in Online Reinforcement Learning.

Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback.

Haolin Liu, Zakaria Mhammedi, Chen-Yu Wei, Julian Zimmert

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Fully Unconstrained Online Learning.

Ashok Cutkosky, Zakaria Mhammedi

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Reinforcement Learning Under Latent Dynamics: Toward Statistical and Algorithmic Modularity.

Philip Amortila, Dylan J. Foster, Nan Jiang, Akshay Krishnamurthy, Zakaria Mhammedi

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

On the Sample Complexity of Imitation Learning for Smoothed Model Predictive Control.

Daniel Pfrommer, Swati Padmanabhan, Kwangjun Ahn, Jack Umenberger, Tobia Marcucci, Zakaria Mhammedi, Ali Jadbabaie

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

2023

Smooth Model Predictive Control with Applications to Statistical Learning.

Kwangjun Ahn, Daniel Pfrommer, Jack Umenberger, Tobia Marcucci, Zakaria Mhammedi, Ali Jadbabaie

CoRR, 2023

Efficient Model-Free Exploration in Low-Rank MDPs.

Zakaria Mhammedi, Adam Block, Dylan J. Foster, Alexander Rakhlin

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

Projection-Free Online Convex Optimization via Efficient Newton Iterations.

Khashayar Gatmiry, Zakaria Mhammedi

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

Model Predictive Control via On-Policy Imitation Learning.

Kwangjun Ahn, Zakaria Mhammedi, Horia Mania, Zhang-Wei Hong, Ali Jadbabaie

Proceedings of the Learning for Dynamics and Control Conference, 2023

Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL.

Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin

Proceedings of the International Conference on Machine Learning, 2023

Quasi-Newton Steps for Efficient Online Exp-Concave Optimization.

Zakaria Mhammedi, Khashayar Gatmiry

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

2022

Exploiting the Curvature of Feasible Sets for Faster Projection-Free Online Learning.

Zakaria Mhammedi

CoRR, 2022

Damped Online Newton Step for Portfolio Selection.

Zakaria Mhammedi, Alexander Rakhlin

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

Efficient Projection-Free Online Convex Optimization with Membership Oracle.

Zakaria Mhammedi

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

2021

Risk Monotonicity in Statistical Learning.

Zakaria Mhammedi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Risk-Monotonicity via Distributional Robustness.

Zakaria Mhammedi, Hisham Husain

CoRR, 2020

PAC-Bayesian Bound for the Conditional Value at Risk.

Zakaria Mhammedi, Benjamin Guedj, Robert C. Williamson

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning the Linear Quadratic Regulator from Nonlinear Observations.

Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Lipschitz and Comparator-Norm Adaptivity in Online Learning.

Zakaria Mhammedi, Wouter M. Koolen

Proceedings of the Conference on Learning Theory, 2020

2019

PAC-Bayes Un-Expected Bernstein Inequality.

Zakaria Mhammedi, Peter Grünwald, Benjamin Guedj

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Lipschitz Adaptivity with Multiple Learning Rates in Online Learning.

Zakaria Mhammedi, Wouter M. Koolen, Tim van Erven

Proceedings of the Conference on Learning Theory, 2019

2018

Constant Regret, Generalized Mixability, and Mirror Descent.

Zakaria Mhammedi, Robert C. Williamson

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Geometry Aware Constrained Optimization Techniques for Deep Learning.

Soumava Kumar Roy, Zakaria Mhammedi, Mehrtash Harandi

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Extracting Real-time Feedback with Neural Networks for Simulation-based Learning.

Xingjun Ma, James Bailey, Sudanthi N. R. Wijewickrema, Shuo Zhou, Zakaria Mhammedi, Yun Zhou, Stephen J. O'Leary

CoRR, 2017

Adversarial Generation of Real-time Feedback with Neural Networks for Simulation-based Training.

Xingjun Ma, Sudanthi N. R. Wijewickrema, Shuo Zhou, Yun Zhou, Zakaria Mhammedi, Stephen J. O'Leary, James Bailey

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections.

Zakaria Mhammedi, Andrew D. Hellicar, Ashfaqur Rahman, James Bailey

Proceedings of the 34th International Conference on Machine Learning, 2017