Zakaria Mhammedi
22 papers · 2017–2025 · 6 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (8) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (6) 🐝 Cross-Pollinator (14)
🏃
Academic Marathon
(8)
🧭
Keyword Pioneer
🌈
Renaissance Researcher
(6)
🐺
Lone Wolf
(4)
🔥
Unstoppable
(9)
💎
Century Club
(22)
❓
The Questioner
🗃️
Keyword Collector
(87)
Conferences
NIPS (9)
COLT (8)
ICML (2)
CVPR (1)
IJCAI (1)
L4DC (1)
Top co-authors
Research topics
Keywords
online convex optimization
(4)
concentration inequality
(3)
mirror descent
(2)
sample-efficient learning
(2)
sample complexity
(2)
markov decision process
(2)
statistical learning
(2)
online learning
(2)
regret bound
(2)
function approximation
(2)
generalization bound
(2)
reinforcement learning
(2)
pac-bayesian theory
(2)
computational complexity
(1)
model predictive control
(1)
adversarial learning
(1)
human-object interaction
(1)
double descent
(1)
representation learning
(1)
value function
(1)
Papers
Sample and Oracle Efficient Reinforcement Learning for MDPs with Linearly-Realizable Value Functions
COLT 2025
Is a Good Foundation Necessary for Efficient Reinforcement Learning? The Computational Role of the Base Model in Exploration
COLT 2025
Online Convex Optimization with a Separation Oracle
COLT 2025
Fully Unconstrained Online Learning
NIPS 2024
The Power of Resets in Online Reinforcement Learning
NIPS 2024
Reinforcement Learning Under Latent Dynamics: Toward Statistical and Algorithmic Modularity
NIPS 2024
Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback
NIPS 2024
Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL
ICML 2023
Quasi-Newton Steps for Efficient Online Exp-Concave Optimization
COLT 2023
Model Predictive Control via On-Policy Imitation Learning
L4DC 2023
Efficient Projection-Free Online Convex Optimization with Membership Oracle
COLT 2022
Damped Online Newton Step for Portfolio Selection
COLT 2022
Risk Monotonicity in Statistical Learning
NIPS 2021
Learning the Linear Quadratic Regulator from Nonlinear Observations
NIPS 2020
PAC-Bayesian Bound for the Conditional Value at Risk
NIPS 2020
Lipschitz and Comparator-Norm Adaptivity in Online Learning
COLT 2020
PAC-Bayes Un-Expected Bernstein Inequality
NIPS 2019
Lipschitz Adaptivity with Multiple Learning Rates in Online Learning
COLT 2019
Constant Regret, Generalized Mixability, and Mirror Descent
NIPS 2018
Geometry Aware Constrained Optimization Techniques for Deep Learning
CVPR 2018
Adversarial Generation of Real-time Feedback with Neural Networks for Simulation-based Training
IJCAI 2017
Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections
ICML 2017