Zakaria Mhammedi

54 papers A* 23Journal 29Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adaptive Matrix Online Learning through Smoothing with Guarantees for Nonsmooth Nonconvex Optimization. CoRR Ruichen Jiang, Zakaria Mhammedi, Mehryar Mohri, Aryan Mokhtari
2026	J	`jnl`	Decoupling Exploration and Policy Optimization: Uncertainty Guided Tree Search for Hard Exploration. CoRR Zakaria Mhammedi, James Cohan
2026	J	`jnl`	End-to-End Efficient RL for Linear Bellman Complete MDPs with Deterministic Transitions. CoRR Zakaria Mhammedi, Alexander Rakhlin, Nneka Okolo
2025	A*	`conf`	Is a Good Foundation Necessary for Efficient Reinforcement Learning? The Computational Role of the Base Model in Exploration. COLT Dylan J. Foster, Zakaria Mhammedi, Dhruv Rohatgi
2025	J	`jnl`	Is a Good Foundation Necessary for Efficient Reinforcement Learning? The Computational Role of the Base Model in Exploration. CoRR Dylan J. Foster, Zakaria Mhammedi, Dhruv Rohatgi
2025	A*	`conf`	Online Convex Optimization with a Separation Oracle. COLT Zakaria Mhammedi
2025	A*	`conf`	Sample and Oracle Efficient Reinforcement Learning for MDPs with Linearly-Realizable Value Functions. COLT Zakaria Mhammedi
2024	A*	`conf`	Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback. NeurIPS Haolin Liu, Zakaria Mhammedi, Chen-Yu Wei, Julian Zimmert
2024	J	`jnl`	Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback. CoRR Haolin Liu, Zakaria Mhammedi, Chen-Yu Wei, Julian Zimmert
2024	A*	`conf`	Fully Unconstrained Online Learning. NeurIPS Ashok Cutkosky, Zakaria Mhammedi
2024	J	`jnl`	Fully Unconstrained Online Learning. CoRR Ashok Cutkosky, Zakaria Mhammedi
2024	J	`jnl`	Improved Sample Complexity of Imitation Learning for Barrier Model Predictive Control. CoRR Daniel Pfrommer, Swati Padmanabhan, Kwangjun Ahn, Jack Umenberger, Tobia Marcucci, Zakaria Mhammedi, Ali Jadbabaie
2024	—	`conf`	On the Sample Complexity of Imitation Learning for Smoothed Model Predictive Control. CDC Daniel Pfrommer, Swati Padmanabhan, Kwangjun Ahn, Jack Umenberger, Tobia Marcucci, Zakaria Mhammedi, Ali Jadbabaie
2024	J	`jnl`	Online Convex Optimization with a Separation Oracle. CoRR Zakaria Mhammedi
2024	A*	`conf`	Reinforcement Learning Under Latent Dynamics: Toward Statistical and Algorithmic Modularity. NeurIPS Philip Amortila, Dylan J. Foster, Nan Jiang, Akshay Krishnamurthy, Zakaria Mhammedi
2024	J	`jnl`	Reinforcement Learning under Latent Dynamics: Toward Statistical and Algorithmic Modularity. CoRR Philip Amortila, Dylan J. Foster, Nan Jiang, Akshay Krishnamurthy, Zakaria Mhammedi
2024	J	`jnl`	Sample- and Oracle-Efficient Reinforcement Learning for MDPs with Linearly-Realizable Value Functions. CoRR Zakaria Mhammedi
2024	A*	`conf`	The Power of Resets in Online Reinforcement Learning. NeurIPS Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin
2024	J	`jnl`	The Power of Resets in Online Reinforcement Learning. CoRR Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin
2023	A*	`conf`	Efficient Model-Free Exploration in Low-Rank MDPs. NeurIPS Zakaria Mhammedi, Adam Block, Dylan J. Foster, Alexander Rakhlin
2023	J	`jnl`	Efficient Model-Free Exploration in Low-Rank MDPs. CoRR Zakaria Mhammedi, Adam Block, Dylan J. Foster, Alexander Rakhlin
2023	—	`conf`	Model Predictive Control via On-Policy Imitation Learning. L4DC Kwangjun Ahn, Zakaria Mhammedi, Horia Mania, Zhang-Wei Hong, Ali Jadbabaie
2023	A*	`conf`	Projection-Free Online Convex Optimization via Efficient Newton Iterations. NeurIPS Khashayar Gatmiry, Zakaria Mhammedi
2023	J	`jnl`	Projection-Free Online Convex Optimization via Efficient Newton Iterations. CoRR Khashayar Gatmiry, Zakaria Mhammedi
2023	A*	`conf`	Quasi-Newton Steps for Efficient Online Exp-Concave Optimization. COLT Zakaria Mhammedi, Khashayar Gatmiry
2023	A*	`conf`	Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL. ICML Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin
2023	J	`jnl`	Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL. CoRR Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin
2023	J	`jnl`	Smooth Model Predictive Control with Applications to Statistical Learning. CoRR Kwangjun Ahn, Daniel Pfrommer, Jack Umenberger, Tobia Marcucci, Zakaria Mhammedi, Ali Jadbabaie
2022	A*	`conf`	Damped Online Newton Step for Portfolio Selection. COLT Zakaria Mhammedi, Alexander Rakhlin
2022	J	`jnl`	Damped Online Newton Step for Portfolio Selection. CoRR Zakaria Mhammedi, Alexander Rakhlin
2022	A*	`conf`	Efficient Projection-Free Online Convex Optimization with Membership Oracle. COLT Zakaria Mhammedi
2022	J	`jnl`	Exploiting the Curvature of Feasible Sets for Faster Projection-Free Online Learning. CoRR Zakaria Mhammedi
2022	J	`jnl`	Model Predictive Control via On-Policy Imitation Learning. CoRR Kwangjun Ahn, Zakaria Mhammedi, Horia Mania, Zhang-Wei Hong, Ali Jadbabaie
2022	J	`jnl`	Quasi-Newton Steps for Efficient Online Exp-Concave Optimization. CoRR Zakaria Mhammedi, Khashayar Gatmiry
2021	J	`jnl`	Efficient Projection-Free Online Convex Optimization with Membership Oracle. CoRR Zakaria Mhammedi
2021	A*	`conf`	Risk Monotonicity in Statistical Learning. NeurIPS Zakaria Mhammedi
2020	A*	`conf`	Learning the Linear Quadratic Regulator from Nonlinear Observations. NeurIPS Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford
2020	J	`jnl`	Learning the Linear Quadratic Regulator from Nonlinear Observations. CoRR Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford
2020	A*	`conf`	Lipschitz and Comparator-Norm Adaptivity in Online Learning. COLT Zakaria Mhammedi, Wouter M. Koolen
2020	J	`jnl`	Lipschitz and Comparator-Norm Adaptivity in Online Learning. CoRR Zakaria Mhammedi, Wouter M. Koolen
2020	A*	`conf`	PAC-Bayesian Bound for the Conditional Value at Risk. NeurIPS Zakaria Mhammedi, Benjamin Guedj, Robert C. Williamson
2020	J	`jnl`	PAC-Bayesian Bound for the Conditional Value at Risk. CoRR Zakaria Mhammedi, Benjamin Guedj, Robert C. Williamson
2020	J	`jnl`	Risk-Monotonicity via Distributional Robustness. CoRR Zakaria Mhammedi, Hisham Husain
2019	A*	`conf`	Lipschitz Adaptivity with Multiple Learning Rates in Online Learning. COLT Zakaria Mhammedi, Wouter M. Koolen, Tim van Erven
2019	J	`jnl`	Lipschitz Adaptivity with Multiple Learning Rates in Online Learning. CoRR Zakaria Mhammedi, Wouter M. Koolen, Tim van Erven
2019	A*	`conf`	PAC-Bayes Un-Expected Bernstein Inequality. NeurIPS Zakaria Mhammedi, Peter Grünwald, Benjamin Guedj
2019	J	`jnl`	PAC-Bayes Un-Expected Bernstein Inequality. CoRR Zakaria Mhammedi, Peter D. Grünwald, Benjamin Guedj
2018	A*	`conf`	Constant Regret, Generalized Mixability, and Mirror Descent. NeurIPS Zakaria Mhammedi, Robert C. Williamson
2018	J	`jnl`	Constant Regret, Generalized Mixability, and Mirror Descent. CoRR Zakaria Mhammedi, Robert C. Williamson
2018	A*	`conf`	Geometry Aware Constrained Optimization Techniques for Deep Learning. CVPR Soumava Kumar Roy, Zakaria Mhammedi, Mehrtash Harandi
2017	A*	`conf`	Adversarial Generation of Real-time Feedback with Neural Networks for Simulation-based Training. IJCAI Xingjun Ma, Sudanthi N. R. Wijewickrema, Shuo Zhou, Yun Zhou, Zakaria Mhammedi, Stephen J. O'Leary, James Bailey
2017	A*	`conf`	Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections. ICML Zakaria Mhammedi, Andrew D. Hellicar, Ashfaqur Rahman, James Bailey
2017	J	`jnl`	Extracting Real-time Feedback with Neural Networks for Simulation-based Learning. CoRR Xingjun Ma, James Bailey, Sudanthi N. R. Wijewickrema, Shuo Zhou, Zakaria Mhammedi, Yun Zhou, Stephen J. O'Leary
2016	J	`jnl`	Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections. CoRR Zakaria Mhammedi, Andrew D. Hellicar, Ashfaqur Rahman, James Bailey

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.