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ORCIDZakaria Mhammedi
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2020 – today
- 2024
[i21]Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin:
The Power of Resets in Online Reinforcement Learning. CoRR abs/2404.15417 (2024)- [i20]Ashok Cutkosky, Zakaria Mhammedi:
Fully Unconstrained Online Learning. CoRR abs/2405.20540 (2024) - [i19]Zakaria Mhammedi:
Sample- and Oracle-Efficient Reinforcement Learning for MDPs with Linearly-Realizable Value Functions. CoRR abs/2409.04840 (2024) - 2023
- [c17]Zakaria Mhammedi, Khashayar Gatmiry:
Quasi-Newton Steps for Efficient Online Exp-Concave Optimization. COLT 2023: 4473-4503 - [c16]Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin:
Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL. ICML 2023: 24659-24700 - [c15]Kwangjun Ahn, Zakaria Mhammedi, Horia Mania, Zhang-Wei Hong, Ali Jadbabaie:
Model Predictive Control via On-Policy Imitation Learning. L4DC 2023: 1493-1505 - [c14]Khashayar Gatmiry, Zakaria Mhammedi:
Projection-Free Online Convex Optimization via Efficient Newton Iterations. NeurIPS 2023 - [c13]Zakaria Mhammedi, Adam Block, Dylan J. Foster, Alexander Rakhlin:
Efficient Model-Free Exploration in Low-Rank MDPs. NeurIPS 2023 - [i18]Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin:
Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL. CoRR abs/2304.05889 (2023) - [i17]Kwangjun Ahn, Daniel Pfrommer, Jack Umenberger, Tobia Marcucci, Zakaria Mhammedi, Ali Jadbabaie:
Smooth Model Predictive Control with Applications to Statistical Learning. CoRR abs/2306.01914 (2023) - [i16]Khashayar Gatmiry, Zakaria Mhammedi:
Projection-Free Online Convex Optimization via Efficient Newton Iterations. CoRR abs/2306.11121 (2023) - [i15]Zakaria Mhammedi, Adam Block, Dylan J. Foster, Alexander Rakhlin:
Efficient Model-Free Exploration in Low-Rank MDPs. CoRR abs/2307.03997 (2023) - 2022
- [c12]Zakaria Mhammedi:
Efficient Projection-Free Online Convex Optimization with Membership Oracle. COLT 2022: 5314-5390 - [c11]Zakaria Mhammedi, Alexander Rakhlin:
Damped Online Newton Step for Portfolio Selection. COLT 2022: 5561-5595 - [i14]Zakaria Mhammedi, Alexander Rakhlin:
Damped Online Newton Step for Portfolio Selection. CoRR abs/2202.07574 (2022) - [i13]Zakaria Mhammedi:
Exploiting the Curvature of Feasible Sets for Faster Projection-Free Online Learning. CoRR abs/2205.11470 (2022) - [i12]Kwangjun Ahn, Zakaria Mhammedi, Horia Mania, Zhang-Wei Hong, Ali Jadbabaie:
Model Predictive Control via On-Policy Imitation Learning. CoRR abs/2210.09206 (2022) - [i11]Zakaria Mhammedi, Khashayar Gatmiry:
Quasi-Newton Steps for Efficient Online Exp-Concave Optimization. CoRR abs/2211.01357 (2022) - 2021
- [c10]Zakaria Mhammedi:
Risk Monotonicity in Statistical Learning. NeurIPS 2021: 10732-10744 - [i10]Zakaria Mhammedi:
Efficient Projection-Free Online Convex Optimization with Membership Oracle. CoRR abs/2111.05818 (2021) - 2020
- [c9]Zakaria Mhammedi, Wouter M. Koolen:
Lipschitz and Comparator-Norm Adaptivity in Online Learning. COLT 2020: 2858-2887 - [c8]Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford:
Learning the Linear Quadratic Regulator from Nonlinear Observations. NeurIPS 2020 - [c7]Zakaria Mhammedi, Benjamin Guedj, Robert C. Williamson:
PAC-Bayesian Bound for the Conditional Value at Risk. NeurIPS 2020 - [i9]Zakaria Mhammedi, Wouter M. Koolen:
Lipschitz and Comparator-Norm Adaptivity in Online Learning. CoRR abs/2002.12242 (2020) - [i8]Zakaria Mhammedi, Benjamin Guedj, Robert C. Williamson:
PAC-Bayesian Bound for the Conditional Value at Risk. CoRR abs/2006.14763 (2020) - [i7]Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford:
Learning the Linear Quadratic Regulator from Nonlinear Observations. CoRR abs/2010.03799 (2020) - [i6]Zakaria Mhammedi, Hisham Husain:
Risk-Monotonicity via Distributional Robustness. CoRR abs/2011.14126 (2020)
2010 – 2019
- 2019
- [c6]Zakaria Mhammedi, Wouter M. Koolen, Tim van Erven:
Lipschitz Adaptivity with Multiple Learning Rates in Online Learning. COLT 2019: 2490-2511 - [c5]Zakaria Mhammedi, Peter Grünwald, Benjamin Guedj:
PAC-Bayes Un-Expected Bernstein Inequality. NeurIPS 2019: 12180-12191 - [i5]Zakaria Mhammedi, Wouter M. Koolen, Tim van Erven:
Lipschitz Adaptivity with Multiple Learning Rates in Online Learning. CoRR abs/1902.10797 (2019) - [i4]Zakaria Mhammedi, Peter D. Grünwald, Benjamin Guedj
:
PAC-Bayes Un-Expected Bernstein Inequality. CoRR abs/1905.13367 (2019) - 2018
- [c4]Soumava Kumar Roy, Zakaria Mhammedi, Mehrtash Harandi:
Geometry Aware Constrained Optimization Techniques for Deep Learning. CVPR 2018: 4460-4469 - [c3]Zakaria Mhammedi, Robert C. Williamson:
Constant Regret, Generalized Mixability, and Mirror Descent. NeurIPS 2018: 7430-7439 - [i3]Zakaria Mhammedi, Robert C. Williamson:
Constant Regret, Generalized Mixability, and Mirror Descent. CoRR abs/1802.06965 (2018) - 2017
- [c2]Zakaria Mhammedi, Andrew D. Hellicar, Ashfaqur Rahman, James Bailey:
Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections. ICML 2017: 2401-2409 - [c1]Xingjun Ma, Sudanthi N. R. Wijewickrema, Shuo Zhou, Yun Zhou, Zakaria Mhammedi, Stephen J. O'Leary, James Bailey:
Adversarial Generation of Real-time Feedback with Neural Networks for Simulation-based Training. IJCAI 2017: 3763-3769 - [i2]Xingjun Ma, James Bailey, Sudanthi N. R. Wijewickrema, Shuo Zhou, Zakaria Mhammedi, Yun Zhou, Stephen J. O'Leary:
Extracting Real-time Feedback with Neural Networks for Simulation-based Learning. CoRR abs/1703.01460 (2017) - 2016
- [i1]Zakaria Mhammedi, Andrew D. Hellicar, Ashfaqur Rahman, James Bailey:
Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections. CoRR abs/1612.00188 (2016)
Coauthor Index
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last updated on 2024-10-10 22:13 CEST by the dblp team
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