Maryam Fazel

Dynamics of Learning under User Choice: Overspecialization and Peer-Model Probing UAI 2026 On The Complexity of Best-Arm Identification in Non-Stationary Linear Bandits COLT 2026 Finite Sample Identification of Partially Observed Bilinear Dynamical Systems L4DC 2025 Keeping up with dynamic attackers: Certifying robustness to adaptive online data poisoning AISTATS 2025 Offline Multi-task Transfer RL with Representational Penalization AISTATS 2025 On Global and Local Convergence of Iterative Linear Quadratic Optimization Algorithms for Discrete Time Nonlinear Control JMLR 2025 A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning ICLR 2024 A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity AISTATS 2024 Efficient Interactive Maximization of BP and Weakly Submodular Objectives UAI 2024 Emergent specialization from participation dynamics and multi-learner retraining AISTATS 2024 Fair Participation via Sequential Policies AAAI 2024 Initializing Services in Interactive ML Systems for Diverse Users NeurIPS 2024 Learning Optimal Tax Design in Nonatomic Congestion Games NeurIPS 2024 Toward Global Convergence of Gradient EM for Over-Paramterized Gaussian Mixture Models NeurIPS 2024 Multiplayer Performative Prediction: Learning in Decision-Dependent Games JMLR 2023 No-Regret Online Prediction with Strategic Experts NeurIPS 2023 Offline Congestion Games: How Feedback Type Affects Data Coverage Requirement ICLR 2023 On Controller Reduction in Linear Quadratic Gaussian Control with Performance Bounds L4DC 2023 Stochastic Contextual Bandits with Long Horizon Rewards AAAI 2023 Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments AAAI 2022 Learning in Congestion Games with Bandit Feedback NeurIPS 2022 Learning in Stochastic Monotone Games with Decision-Dependent Data AISTATS 2022 Near-Optimal Randomized Exploration for Tabular Markov Decision Processes NeurIPS 2022 Differentially Private Monotone Submodular Maximization Under Matroid and Knapsack Constraints AISTATS 2021 Online DR-Submodular Maximization: Minimizing Regret and Constraint Violation AAAI 2021 Selective Sampling for Online Best-arm Identification NeurIPS 2021 Towards Sample-efficient Overparameterized Meta-learning NeurIPS 2021 A Single Recipe for Online Submodular Maximization with Adversarial or Stochastic Constraints NeurIPS 2020 Finite Sample System Identification: Optimal Rates and the Role of Regularization L4DC 2020 Online Continuous DR-Submodular Maximization with Long-Term Budget Constraints AISTATS 2020 Escaping from saddle points on Riemannian manifolds NeurIPS 2019 Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator ICML 2018 Designing smoothing functions for improved worst-case competitive ratio in online optimization NeurIPS 2016 Exploiting Tradeoffs for Exact Recovery in Heterogeneous Stochastic Block Models NeurIPS 2016 Learning Graphical Models With Hubs JMLR 2014 Node-Based Learning of Multiple Gaussian Graphical Models JMLR 2014 Similarity-based Clustering by Left-Stochastic Matrix Factorization JMLR 2013 Iterative Reweighted Algorithms for Matrix Rank Minimization JMLR 2012 Structured Learning of Gaussian Graphical Models NeurIPS 2012