Publications

Zak Mhammedi, Adam Block, Dylan J. Foster, Alexander Rakhlin (2023). Efficient Model-Free Exploration in Low-Rank MDPs. Pre-Print 2023.

Zak Mhammedi, Gatmiry Khashayar (2023). Quasi-Newton Steps for Efficient Online Exp-Concave Optimization. arXiv preprint arXiv:2211.01357.

Zak Mhammedi, Dylan J. Foster, Alexander Rakhlin (2023). Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL. ICML 2023.

Peter D. Grunwald, Muriel F. Perez-Ortiz, Zak Mhammedi (2023). Exponential Stochastic Inequality. arXiv preprint arXiv:2304.14217.

Kwangjun Ahn, Zak Mhammedi, Horia Mania, Zhang-Wei Hong, Ali Jadbabaie (2022). Model Predictive Control via On-Policy Imitation Learning. arXiv preprint arXiv:2210.09206.

Zak Mhammedi (2022). Exploiting the Curvature of Feasible Sets for Faster Projection-Free Online Learning. arXiv.

Zak Mhammedi, Alexander Rakhlin (2022). Damped Online Newton Step for Portfolio Selection. arXiv preprint arXiv:2202.07574.

Zak Mhammedi (2021). Efficient Projection-Free Online Convex Optimization with Membership Oracle. arXiv:2111.05818 [math, cs].

Zak Mhammedi (2021). Risk-Monotonicity in Statistical Learning. arXiv:2011.14126 [cs, stat].

Zak Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford (2020). Learning the Linear Quadratic Regulator from Nonlinear Observations. arXiv:2010.03799 [cs, math, stat].

Pre-Print Poster

Zak Mhammedi, Wouter M. Koolen (2020). Lipschitz and Comparator-Norm Adaptivity in Online Learning. Conference on Learning Theory.

Zak Mhammedi, Benjamin Guedj, Robert C. Williamson (2020). PAC-Bayesian Bound for the Conditional Value at Risk. arXiv:2006.14763 [cs, stat].

Pre-Print Poster

Zak Mhammedi, Wouter M. Koolen, Tim Van Erven (2019). Lipschitz Adaptivity with Multiple Learning Rates in Online Learning. Conference on Learning Theory.

Zak Mhammedi, Peter Grünwald, Benjamin Guedj (2019). PAC-Bayes Un-Expected Bernstein Inequality. Advances in Neural Information Processing Systems 32.

Soumava Kumar Roy, Zak Mhammedi, Mehrtash Harandi (2018). Geometry Aware Constrained Optimization Techniques for Deep Learning. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Zak Mhammedi, Robert C Williamson (2018). Constant Regret, Generalized Mixability, and Mirror Descent. NeurIPS 2018.

Zak Mhammedi, Andrew Hellicar, Ashfaqur Rahman, James Bailey (2017). Efficient orthogonal parametrisation of Recurrent Neural Networks using householder reflections. Proceedings of the 34th International Conference on Machine Learning - Volume 70.

Xingjun Ma, Sudanthi Wijewickrema, Shuo Zhou, Yun Zhou, Zakaria Mhammedi, Stephen O'Leary, James Bailey (2017). Adversarial Generation of Real-time Feedback with Neural Networks for Simulation-based Training. Electronic proceedings of IJCAI 2017.