Timezone: »
Author Information
Alireza Fallah (MIT)
Aryan Mokhtari (UT Austin)
Asuman Ozdaglar (Massachusetts Institute of Technology)
Asu Ozdaglar received the B.S. degree in electrical engineering from the Middle East Technical University, Ankara, Turkey, in 1996, and the S.M. and the Ph.D. degrees in electrical engineering and computer science from the Massachusetts Institute of Technology, Cambridge, in 1998 and 2003, respectively. She is currently a professor in the Electrical Engineering and Computer Science Department at the Massachusetts Institute of Technology. She is also the director of the Laboratory for Information and Decision Systems. Her research expertise includes optimization theory, with emphasis on nonlinear programming and convex analysis, game theory, with applications in communication, social, and economic networks, distributed optimization and control, and network analysis with special emphasis on contagious processes, systemic risk and dynamic control. Professor Ozdaglar is the recipient of a Microsoft fellowship, the MIT Graduate Student Council Teaching award, the NSF Career award, the 2008 Donald P. Eckman award of the American Automatic Control Council, the Class of 1943 Career Development Chair, the inaugural Steven and Renee Innovation Fellowship, and the 2014 Spira teaching award. She served on the Board of Governors of the Control System Society in 2010 and was an associate editor for IEEE Transactions on Automatic Control. She is currently the area co-editor for a new area for the journal Operations Research, entitled "Games, Information and Networks. She is the co-author of the book entitled âConvex Analysis and Optimizationâ (Athena Scientific, 2003).
More from the Same Authors
-
2022 : Conditional gradient-based method for bilevel optimization with convex lower-level problem »
Ruichen Jiang · Nazanin Abolfazli · Aryan Mokhtari · Erfan Yazdandoost Hamedani -
2022 : Statistical and Computational Complexities of BFGS Quasi-Newton Method for Generalized Linear Models »
Qiujiang Jin · Aryan Mokhtari · Nhat Ho · Tongzheng Ren -
2022 : Smoothed-SGDmax: A Stability-Inspired Algorithm to Improve Adversarial Generalization »
Jiancong Xiao · Jiawei Zhang · Zhiquan Luo · Asuman Ozdaglar -
2023 Poster: Time-Reversed Dissipation Induces Duality Between Minimizing Gradient Norm and Function Value »
Kim · Asuman Ozdaglar · Chanwoo Park · Ernest Ryu -
2023 Poster: Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization »
Ruichen Jiang · Aryan Mokhtari -
2023 Poster: A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games »
Zaiwei Chen · Kaiqing Zhang · Eric Mazumdar · Asuman Ozdaglar · Adam Wierman -
2023 Poster: Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem »
Jincheng Cao · Ruichen Jiang · Nazanin Abolfazli · Erfan Yazdandoost Hamedani · Aryan Mokhtari -
2023 Poster: Multi-Player Zero-Sum Markov Games with Networked Local Interactions »
Chanwoo Park · Kaiqing Zhang · Asuman Ozdaglar -
2023 Poster: Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing »
Nived Rajaraman · Fnu Devvrit · Aryan Mokhtari · Kannan Ramchandran -
2022 Poster: What is a Good Metric to Study Generalization of Minimax Learners? »
Asuman Ozdaglar · Sarath Pattathil · Jiawei Zhang · Kaiqing Zhang -
2022 Poster: Bridging Central and Local Differential Privacy in Data Acquisition Mechanisms »
Alireza Fallah · Ali Makhdoumi · azarakhsh malekian · Asuman Ozdaglar -
2022 Poster: FedAvg with Fine Tuning: Local Updates Lead to Representation Learning »
Liam Collins · Hamed Hassani · Aryan Mokhtari · Sanjay Shakkottai -
2021 : Q&A with Professor Asu Ozdaglar »
Asuman Ozdaglar -
2021 : Keynote Talk: Personalization in Federated Learning: Adaptation and Clustering (Asu Ozdaglar) »
Asuman Ozdaglar -
2021 Poster: Decentralized Q-learning in Zero-sum Markov Games »
Muhammed Sayin · Kaiqing Zhang · David Leslie · Tamer Basar · Asuman Ozdaglar -
2021 Poster: Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach »
Qiujiang Jin · Aryan Mokhtari -
2021 Poster: On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement Learning »
Alireza Fallah · Kristian Georgiev · Aryan Mokhtari · Asuman Ozdaglar -
2020 Poster: Task-Robust Model-Agnostic Meta-Learning »
Liam Collins · Aryan Mokhtari · Sanjay Shakkottai -
2020 Poster: Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient Tracking »
Isidoros Tziotis · Constantine Caramanis · Aryan Mokhtari -
2020 Poster: Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach »
Alireza Fallah · Aryan Mokhtari · Asuman Ozdaglar -
2020 Poster: Submodular Meta-Learning »
Arman Adibi · Aryan Mokhtari · Hamed Hassani -
2019 : Invited talk: Aryan Mokhtari (UT Austin) »
Aryan Mokhtari -
2019 Poster: A Universally Optimal Multistage Accelerated Stochastic Gradient Method »
Necdet Serhat Aybat · Alireza Fallah · Mert Gurbuzbalaban · Asuman Ozdaglar -
2019 Poster: Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match »
Amin Karbasi · Hamed Hassani · Aryan Mokhtari · Zebang Shen -
2019 Poster: Robust and Communication-Efficient Collaborative Learning »
Amirhossein Reisizadeh · Hossein Taheri · Aryan Mokhtari · Hamed Hassani · Ramtin Pedarsani -
2018 Poster: Direct Runge-Kutta Discretization Achieves Acceleration »
Jingzhao Zhang · Aryan Mokhtari · Suvrit Sra · Ali Jadbabaie -
2018 Spotlight: Direct Runge-Kutta Discretization Achieves Acceleration »
Jingzhao Zhang · Aryan Mokhtari · Suvrit Sra · Ali Jadbabaie -
2018 Poster: Escaping Saddle Points in Constrained Optimization »
Aryan Mokhtari · Asuman Ozdaglar · Ali Jadbabaie -
2018 Spotlight: Escaping Saddle Points in Constrained Optimization »
Aryan Mokhtari · Asuman Ozdaglar · Ali Jadbabaie -
2017 Poster: When Cyclic Coordinate Descent Outperforms Randomized Coordinate Descent »
Mert Gurbuzbalaban · Asuman Ozdaglar · Pablo A Parrilo · Nuri Vanli -
2017 Spotlight: When Cyclic Coordinate Descent Outperforms Randomized Coordinate Descent »
Mert Gurbuzbalaban · Asuman Ozdaglar · Pablo A Parrilo · Nuri Vanli -
2015 Invited Talk: Incremental Methods for Additive Cost Convex Optimization »
Asuman Ozdaglar -
2013 Poster: Computing the Stationary Distribution Locally »
Christina Lee · Asuman Ozdaglar · Devavrat Shah