← Authors

Asuman Ozdaglar

24 papers · 2013–2024 · 6 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (11) πŸ—ΊοΈ Taxonomy Completionist (12) 🐝 Cross-Pollinator (5) 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (6) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸ”¬ Deep Specialist (12) πŸ—ƒοΈ Keyword Collector (117) ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ’Ž Century Club (24) πŸ”₯ Unstoppable (8) πŸ“ˆ Trend Setter ❓ The Questioner (2)

Conferences

NIPS (13) AISTATS (5) ICML (3) COLT (1) JMLR (1) L4DC (1)

Top co-authors

Alireza Fallah (8) Aryan Mokhtari (7) Kaiqing Zhang (5) Sarath Pattathil (4) Mert Gurbuzbalaban (3) Farzan Farnia (3) Ali Jadbabaie (2) Chanwoo Park (2) Christina E. Lee (1) Yonina Eldar (1)

Keywords

convex optimization (5) minimax optimization (5) zero-sum game (5) saddle point (4) nonconvex optimization (3) generalization bound (3) model-agnostic meta-learning (3) nash equilibrium (3) markov game (3) stochastic gradient descent (2) generative adversarial network (2) federated learning (2) gradient descent ascent (2) algorithmic stability (2) convergence rate (2) distributed learning (2) stochastic gradient (2) stochastic optimization (2) gradient descent (2) proximal point method (2)

Papers

EM for Mixture of Linear Regression with Clustered Data AISTATS 2024
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games NIPS 2023
Symmetric (Optimistic) Natural Policy Gradient for Multi-Agent Learning with Parameter Convergence AISTATS 2023
Time-Reversed Dissipation Induces Duality Between Minimizing Gradient Norm and Function Value NIPS 2023
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions NIPS 2023
Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks JMLR 2022
Bridging Central and Local Differential Privacy in Data Acquisition Mechanisms NIPS 2022
What is a Good Metric to Study Generalization of Minimax Learners? NIPS 2022
Train simultaneously, generalize better: Stability of gradient-based minimax learners ICML 2021
On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement Learning NIPS 2021
A Wasserstein Minimax Framework for Mixed Linear Regression ICML 2021
Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks NIPS 2021
Decentralized Q-learning in Zero-sum Markov Games NIPS 2021
Bayesian Learning with Adaptive Load Allocation Strategies L4DC 2020
Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach NIPS 2020
On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms AISTATS 2020
A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach AISTATS 2020
Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems COLT 2020
Do GANs always have Nash equilibria? ICML 2020
A Universally Optimal Multistage Accelerated Stochastic Gradient Method NIPS 2019
Efficient Nonconvex Empirical Risk Minimization via Adaptive Sample Size Methods AISTATS 2019
Escaping Saddle Points in Constrained Optimization NIPS 2018
When Cyclic Coordinate Descent Outperforms Randomized Coordinate Descent NIPS 2017
Computing the Stationary Distribution Locally NIPS 2013