Asuman E. Ozdaglar

ORCID

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 130

Top Venues

Massachusetts Institute of Technology, Cambridge, MA, USA (PHD)

Education History

Massachusetts Institute of Technology, Cambridge, MA, USA

PHD

Publications

Daniel P. Huttenlocher, Hannah Li, Liang Lyu, Asuman E. Ozdaglar, James Siderius
Matching of Users and Creators in Two-Sided Markets with Departures. CoRR (2024)
Mingyang Liu, Gabriele Farina, Asuman E. Ozdaglar
LiteEFG: An Efficient Python Library for Solving Extensive-form Games. CoRR (2024)
Chanwoo Park, Mingyang Liu, Dingwen Kong, Kaiqing Zhang, Asuman E. Ozdaglar
RLHF from Heterogeneous Feedback via Personalization and Preference Aggregation. CoRR (2024)
Daron Acemoglu, Ali Makhdoumi, Azarakhsh Malekian, Asuman E. Ozdaglar
Testing, Voluntary Social Distancing, and the Spread of an Infection. Oper. Res. 72 (2) (2024)
Amirhossein Reisizadeh, Khashayar Gatmiry, Asuman E. Ozdaglar
EM for Mixture of Linear Regression with Clustered Data. AISTATS (2024)
Jiancong Xiao, Jiawei Zhang, Zhi-Quan Luo, Asuman E. Ozdaglar
Uniformly Stable Algorithms for Adversarial Training and Beyond. CoRR (2024)
Chanwoo Park, Xiangyu Liu, Asuman E. Ozdaglar, Kaiqing Zhang
Do LLM Agents Have Regret? A Case Study in Online Learning and Games. CoRR (2024)
Kihyun Kim, Jiawei Zhang, Asuman E. Ozdaglar, Pablo A. Parrilo
A Unified Linear Programming Framework for Offline Reward Learning from Human Demonstrations and Feedback. CoRR (2024)
Daron Acemoglu, Alireza Fallah, Andrea Giometto, Daniel P. Huttenlocher, Asuman E. Ozdaglar, Francesca Parise, Sarath Pattathil
Optimal adaptive testing for epidemic control: Combining molecular and serology tests. Autom. 160 (2024)
Alireza Fallah, Ali Makhdoumi, Azarakhsh Malekian, Asuman E. Ozdaglar
Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms. Oper. Res. 72 (3) (2024)
Fathima Zarin Faizal, Asuman E. Ozdaglar, Martin J. Wainwright
Finite-Sample Guarantees for Best-Response Learning Dynamics in Zero-Sum Matrix Games. CoRR (2024)
Leonardo Cianfanelli, Giacomo Como, Asuman E. Ozdaglar, Francesca Parise
Optimal Intervention in Transportation Networks. IEEE Trans. Autom. Control. 68 (12) (2023)
Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games. NeurIPS (2023)
Amirhossein Reisizadeh, Khashayar Gatmiry, Asuman E. Ozdaglar
EM for Mixture of Linear Regression with Clustered Data. CoRR (2023)
Chanwoo Park, Kaiqing Zhang, Asuman E. Ozdaglar
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions. NeurIPS (2023)
Daron Acemoglu, Asuman E. Ozdaglar, Sarath Pattathil
Learning, Diversity and Adaptation in Changing Environments: The Role of Weak Links. CoRR (2023)
Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games. CoRR (2023)
Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman
Two-Timescale Q-Learning with Function Approximation in Zero-Sum Stochastic Games. CoRR (2023)
Chanwoo Park, Kaiqing Zhang, Asuman E. Ozdaglar
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions. CoRR (2023)
Mingyang Liu, Asuman E. Ozdaglar, Tiancheng Yu, Kaiqing Zhang
The Power of Regularization in Solving Extensive-Form Games. ICLR (2023)
Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang
Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation. ICML (2023)
Sarath Pattathil, Kaiqing Zhang, Asuman E. Ozdaglar
Symmetric (Optimistic) Natural Policy Gradient for Multi-Agent Learning with Parameter Convergence. AISTATS (2023)
Jaeyeon Kim, Asuman E. Ozdaglar, Chanwoo Park, Ernest K. Ryu
Time-Reversed Dissipation Induces Duality Between Minimizing Gradient Norm and Function Value. NeurIPS (2023)
Muhammed O. Sayin, Kaiqing Zhang, Asuman E. Ozdaglar
Fictitious Play in Markov Games with Single Controller. EC (2022)
Alireza Fallah, Ali Makhdoumi, Azarakhsh Malekian, Asuman E. Ozdaglar
Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms. CoRR (2022)
Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang
Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation. CoRR (2022)
Hoi-To Wai, Yonina C. Eldar, Asuman E. Ozdaglar, Anna Scaglione
Community Inference From Partially Observed Graph Signals: Algorithms and Analysis. IEEE Trans. Signal Process. 70 (2022)
Muhammed O. Sayin, Francesca Parise, Asuman E. Ozdaglar
Fictitious Play in Zero-Sum Stochastic Games. SIAM J. Control. Optim. 60 (4) (2022)
Sarath Pattathil, Kaiqing Zhang, Asuman E. Ozdaglar
Symmetric (Optimistic) Natural Policy Gradient for Multi-agent Learning with Parameter Convergence. CoRR (2022)
Mohamed Mostagir, Asuman E. Ozdaglar, James Siderius
When Is Society Susceptible to Manipulation? Manag. Sci. 68 (10) (2022)
Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang
What is a Good Metric to Study Generalization of Minimax Learners? NeurIPS (2022)
Alireza Fallah, Ali Makhdoumi, Azarakhsh Malekian, Asuman E. Ozdaglar
Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms. EC (2022)
Mingyang Liu, Asuman E. Ozdaglar, Tiancheng Yu, Kaiqing Zhang
The Power of Regularization in Solving Extensive-Form Games. CoRR (2022)
Murat A. Erdogdu, Asuman E. Ozdaglar, Pablo A. Parrilo, Nuri Denizcan Vanli
Convergence rate of block-coordinate maximization Burer-Monteiro method for solving large SDPs. Math. Program. 195 (1) (2022)
Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang
What is a Good Metric to Study Generalization of Minimax Learners? CoRR (2022)
Muhammed O. Sayin, Kaiqing Zhang, Asuman E. Ozdaglar
Fictitious Play in Markov Games with Single Controller. CoRR (2022)
Alireza Fallah, Ali Makhdoumi, Azarakhsh Malekian, Asuman E. Ozdaglar
Bridging Central and Local Differential Privacy in Data Acquisition Mechanisms. NeurIPS (2022)
Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar, Umut Simsekli, Lingjiong Zhu
Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks. J. Mach. Learn. Res. 23 (2022)
Manxi Wu, Saurabh Amin, Asuman E. Ozdaglar
Convergence and Stability of Coupled Belief-Strategy Learning Dynamics in Continuous Games. CoRR (2022)
Francesca Parise, Asuman E. Ozdaglar
Analysis and Interventions in Large Network Games. Annu. Rev. Control. Robotics Auton. Syst. 4 (2021)
Farzan Farnia, Asuman E. Ozdaglar
Train simultaneously, generalize better: Stability of gradient-based minimax learners. ICML (2021)
Manxi Wu, Saurabh Amin, Asuman E. Ozdaglar
Value of Information in Bayesian Routing Games. Oper. Res. 69 (1) (2021)
Leonardo Cianfanelli, Francesca Parise, Daron Acemoglu, Giacomo Como, Asuman E. Ozdaglar
Lockdown interventions in SIR models: Is the reproduction number the right control variable? CDC (2021)
Mert Gürbüzbalaban, Asuman E. Ozdaglar, Pablo A. Parrilo
Why random reshuffling beats stochastic gradient descent. Math. Program. 186 (1) (2021)
Alireza Fallah, Aryan Mokhtari, Asuman E. Ozdaglar
Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks. CoRR (2021)
Leonardo Cianfanelli, Giacomo Como, Asuman E. Ozdaglar, Francesca Parise
Optimal intervention in traffic networks. CoRR (2021)
Asuman E. Ozdaglar, Muhammed O. Sayin, Kaiqing Zhang
Independent Learning in Stochastic Games. CoRR (2021)
Manxi Wu, Saurabh Amin, Asuman E. Ozdaglar
Multi-agent Bayesian Learning with Best Response Dynamics: Convergence and Stability. CoRR (2021)
Theo Diamandis, Yonina C. Eldar, Alireza Fallah, Farzan Farnia, Asuman E. Ozdaglar
A Wasserstein Minimax Framework for Mixed Linear Regression. ICML (2021)
Daron Acemoglu, Alireza Fallah, A. Giometto, D. Huttenlocher, Asuman E. Ozdaglar, Francesca Parise, Sarath Pattathil
Optimal adaptive testing for epidemic control: combining molecular and serology tests. CoRR (2021)
Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie, Tamer Basar, Asuman E. Ozdaglar
Decentralized Q-Learning in Zero-sum Markov Games. CoRR (2021)
Theo Diamandis, Yonina C. Eldar, Alireza Fallah, Farzan Farnia, Asuman E. Ozdaglar
A Wasserstein Minimax Framework for Mixed Linear Regression. CoRR (2021)
Alireza Fallah, Kristian Georgiev, Aryan Mokhtari, Asuman E. Ozdaglar
On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement Learning. NeurIPS (2021)
Alireza Fallah, Aryan Mokhtari, Asuman E. Ozdaglar
Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks. NeurIPS (2021)
Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie, Tamer Basar, Asuman E. Ozdaglar
Decentralized Q-learning in Zero-sum Markov Games. NeurIPS (2021)
Alireza Fallah, Asuman E. Ozdaglar, Sarath Pattathil
An Optimal Multistage Stochastic Gradient Method for Minimax Problems. CDC (2020)
Alireza Fallah, Aryan Mokhtari, Asuman E. Ozdaglar
Provably Convergent Policy Gradient Methods for Model-Agnostic Meta-Reinforcement Learning. CoRR (2020)
Aryan Mokhtari, Asuman E. Ozdaglar, Sarath Pattathil
A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach. AISTATS (2020)
Farzan Farnia, Asuman E. Ozdaglar
Train simultaneously, generalize better: Stability of gradient-based minimax learners. CoRR (2020)
Alireza Fallah, Aryan Mokhtari, Asuman E. Ozdaglar
Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach. NeurIPS (2020)
Alireza Fallah, Asuman E. Ozdaglar, Sarath Pattathil
An Optimal Multistage Stochastic Gradient Method for Minimax Problems. CoRR (2020)
Hoi-To Wai, Santiago Segarra, Asuman E. Ozdaglar, Anna Scaglione, Ali Jadbabaie
Blind Community Detection From Low-Rank Excitations of a Graph Filter. IEEE Trans. Signal Process. 68 (2020)
Alireza Fallah, Aryan Mokhtari, Asuman E. Ozdaglar
Personalized Federated Learning: A Meta-Learning Approach. CoRR (2020)
Manxi Wu, Saurabh Amin, Asuman E. Ozdaglar
Multi-agent Bayesian Learning with Adaptive Strategies: Convergence and Stability. CoRR (2020)
Aryan Mokhtari, Asuman E. Ozdaglar, Sarath Pattathil
Convergence Rate of 풪(1/k) for Optimistic Gradient and Extragradient Methods in Smooth Convex-Concave Saddle Point Problems. SIAM J. Optim. 30 (4) (2020)
Noah Golowich, Sarath Pattathil, Constantinos Daskalakis, Asuman E. Ozdaglar
Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems. COLT (2020)
Necdet Serhat Aybat, Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar
Robust Accelerated Gradient Methods for Smooth Strongly Convex Functions. SIAM J. Optim. 30 (1) (2020)
Emily Meigs, Francesca Parise, Asuman E. Ozdaglar, Daron Acemoglu
Optimal dynamic information provision in traffic routing. CoRR (2020)
Farzan Farnia, Asuman E. Ozdaglar
Do GANs always have Nash equilibria? ICML (2020)
Asuman E. Ozdaglar, Devavrat Shah, Christina Lee Yu
Asynchronous Approximation of a Single Component of the Solution to a Linear System. IEEE Trans. Netw. Sci. Eng. 7 (3) (2020)
Farzan Farnia, Asuman E. Ozdaglar
GANs May Have No Nash Equilibria. CoRR (2020)
Muhammed O. Sayin, Francesca Parise, Asuman E. Ozdaglar
Fictitious play in zero-sum stochastic games. CoRR (2020)
Alireza Fallah, Aryan Mokhtari, Asuman E. Ozdaglar
On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms. AISTATS (2020)
Mert Gürbüzbalaban, Asuman E. Ozdaglar, Nuri Denizcan Vanli, Stephen J. Wright
Randomness and permutations in coordinate descent methods. Math. Program. 181 (2) (2020)
Noah Golowich, Sarath Pattathil, Constantinos Daskalakis, Asuman E. Ozdaglar
Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems. CoRR (2020)
Manxi Wu, Saurabh Amin, Asuman E. Ozdaglar
Bayesian Learning with Adaptive Load Allocation Strategies. L4DC (2020)
Aryan Mokhtari, Asuman E. Ozdaglar, Sarath Pattathil
Proximal Point Approximations Achieving a Convergence Rate of O(1/k) for Smooth Convex-Concave Saddle Point Problems: Optimistic Gradient and Extra-gradient Methods. CoRR (2019)
Necdet Serhat Aybat, Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar
A Universally Optimal Multistage Accelerated Stochastic Gradient Method. CoRR (2019)
Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar, Umut Simsekli, Lingjiong Zhu
Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks. CoRR (2019)
Hoi-To Wai, Yonina C. Eldar, Asuman E. Ozdaglar, Anna Scaglione
Community Inference from Graph Signals with Hidden Nodes. ICASSP (2019)
Weijie Liu, Aryan Mokhtari, Asuman E. Ozdaglar, Sarath Pattathil, Zebang Shen, Nenggan Zheng
A Decentralized Proximal Point-type Method for Saddle Point Problems. CoRR (2019)
Elie M. Adam, Munther A. Dahleh, Asuman E. Ozdaglar
Interconnection and Memory in Linear Time-Invariant Systems. IEEE Trans. Autom. Control. 64 (5) (2019)
Necdet Serhat Aybat, Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar
A Universally Optimal Multistage Accelerated Stochastic Gradient Method. NeurIPS (2019)
Alireza Fallah, Aryan Mokhtari, Asuman E. Ozdaglar
On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms. CoRR (2019)
Aryan Mokhtari, Asuman E. Ozdaglar, Ali Jadbabaie
Efficient Nonconvex Empirical Risk Minimization via Adaptive Sample Size Methods. AISTATS (2019)
Aryan Mokhtari, Asuman E. Ozdaglar, Sarath Pattathil
A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach. CoRR (2019)
Francesca Parise, Asuman E. Ozdaglar
Graphon Games. EC (2019)
Emily Meigs, Francesca Parise, Asuman E. Ozdaglar
Learning in repeated stochastic network aggregative games. CDC (2019)
Mert Gürbüzbalaban, Asuman E. Ozdaglar, Pablo A. Parrilo
Convergence Rate of Incremental Gradient and Incremental Newton Methods. SIAM J. Optim. 29 (4) (2019)
Francesca Parise, Asuman E. Ozdaglar
A variational inequality framework for network games: Existence, uniqueness, convergence and sensitivity analysis. Games Econ. Behav. 114 (2019)
Aryan Mokhtari, Asuman E. Ozdaglar, Ali Jadbabaie
Escaping Saddle Points in Constrained Optimization. NeurIPS (2018)
Manxi Wu, Saurabh Amin, Asuman E. Ozdaglar
Value of Information Systems in Routing Games. CoRR (2018)
Necdet Serhat Aybat, Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar
Robust Accelerated Gradient Methods for Smooth Strongly Convex Functions. CoRR (2018)
Ozan Candogan, Asuman E. Ozdaglar, Pablo A. Parrilo
Pricing Equilibria and Graphical Valuations. ACM Trans. Economics and Comput. 6 (1) (2018)
Hoi-To Wai, Santiago Segarra, Asuman E. Ozdaglar, Anna Scaglione, Ali Jadbabaie
Community Detection from Low-Rank Excitations of a Graph Filter. ICASSP (2018)
Murat A. Erdogdu, Asuman E. Ozdaglar, Pablo A. Parrilo, Nuri Denizcan Vanli
Convergence Rate of Block-Coordinate Maximization Burer-Monteiro Method for Solving Large SDPs. CoRR (2018)
N. Denizcan Vanli, Mert Gürbüzbalaban, Asuman E. Ozdaglar
Global Convergence Rate of Proximal Incremental Aggregated Gradient Methods. SIAM J. Optim. 28 (2) (2018)
Hoi-To Wai, Asuman E. Ozdaglar, Anna Scaglione
Identifying Susceptible Agents in Time Varying Opinion Dynamics Through Compressive Measurements. ICASSP (2018)
Francesca Parise, Asuman E. Ozdaglar
Graphon games. CoRR (2018)
Aryan Mokhtari, Asuman E. Ozdaglar, Ali Jadbabaie
Escaping Saddle Points in Constrained Optimization. CoRR (2018)

Asuman E. Ozdaglar.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Asuman E. Ozdaglar