Sarath Pattathil

36 papers A* 5A 2B 2Journal 22Unranked 4

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Autobidders with Budget and ROI Constraints: Efficiency, Regret, and Pacing Dynamics. COLT Brendan Lucier, Sarath Pattathil, Aleksandrs Slivkins, Mengxiao Zhang
2024	J	`jnl`	Optimal adaptive testing for epidemic control: Combining molecular and serology tests. Autom. Daron Acemoglu, Alireza Fallah, Andrea Giometto, Daniel P. Huttenlocher, Asuman E. Ozdaglar, Francesca Parise, Sarath Pattathil
2023	J	`jnl`	Autobidders with Budget and ROI Constraints: Efficiency, Regret, and Pacing Dynamics. CoRR Brendan Lucier, Sarath Pattathil, Aleksandrs Slivkins, Mengxiao Zhang
2023	J	`jnl`	Learning, Diversity and Adaptation in Changing Environments: The Role of Weak Links. CoRR Daron Acemoglu, Asuman E. Ozdaglar, Sarath Pattathil
2023	—	`—`	Optimization and Generalization of Minimax Algorithms Sarath Pattathil
2023	A*	`conf`	Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation. ICML Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang
2023	A	`conf`	Symmetric (Optimistic) Natural Policy Gradient for Multi-Agent Learning with Parameter Convergence. AISTATS Sarath Pattathil, Kaiqing Zhang, Asuman E. Ozdaglar
2022	J	`jnl`	Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation. CoRR Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang
2022	J	`jnl`	Symmetric (Optimistic) Natural Policy Gradient for Multi-agent Learning with Parameter Convergence. CoRR Sarath Pattathil, Kaiqing Zhang, Asuman E. Ozdaglar
2022	A*	`conf`	What is a Good Metric to Study Generalization of Minimax Learners? NeurIPS Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang
2022	J	`jnl`	What is a Good Metric to Study Generalization of Minimax Learners? CoRR Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang
2022	J	`jnl`	Whittle indexability in egalitarian processor sharing systems. Ann. Oper. Res. Vivek S. Borkar, Sarath Pattathil
2021	J	`jnl`	Optimal adaptive testing for epidemic control: combining molecular and serology tests. CoRR Daron Acemoglu, Alireza Fallah, Andrea Giometto, Daniel P. Huttenlocher, Asuman E. Ozdaglar, Francesca Parise, Sarath Pattathil
2020	A	`conf`	A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach. AISTATS Aryan Mokhtari, Asuman E. Ozdaglar, Sarath Pattathil
2020	—	`conf`	An Optimal Multistage Stochastic Gradient Method for Minimax Problems. CDC Alireza Fallah, Asuman E. Ozdaglar, Sarath Pattathil
2020	J	`jnl`	An Optimal Multistage Stochastic Gradient Method for Minimax Problems. CoRR Alireza Fallah, Asuman E. Ozdaglar, Sarath Pattathil
2020	J	`jnl`	Convergence Rate of 풪(1/k) for Optimistic Gradient and Extragradient Methods in Smooth Convex-Concave Saddle Point Problems. SIAM J. Optim. Aryan Mokhtari, Asuman E. Ozdaglar, Sarath Pattathil
2020	J	`jnl`	Jordan centre in random trees: persistence and distance to root. J. Complex Networks Sarath Pattathil, Nikhil Karamchandani, Dhruti Shah
2020	A*	`conf`	Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems. COLT Noah Golowich, Sarath Pattathil, Constantinos Daskalakis, Asuman E. Ozdaglar
2020	J	`jnl`	Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems. CoRR Noah Golowich, Sarath Pattathil, Constantinos Daskalakis, Asuman E. Ozdaglar
2020	A*	`conf`	Tight last-iterate convergence rates for no-regret learning in multi-player games. NeurIPS Noah Golowich, Sarath Pattathil, Constantinos Daskalakis
2020	J	`jnl`	Tight last-iterate convergence rates for no-regret learning in multi-player games. CoRR Noah Golowich, Sarath Pattathil, Constantinos Daskalakis
2019	J	`jnl`	A Decentralized Proximal Point-type Method for Saddle Point Problems. CoRR Weijie Liu, Aryan Mokhtari, Asuman E. Ozdaglar, Sarath Pattathil, Zebang Shen, Nenggan Zheng
2019	J	`jnl`	A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach. CoRR Aryan Mokhtari, Asuman E. Ozdaglar, Sarath Pattathil
2019	J	`jnl`	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 Aryan Mokhtari, Asuman E. Ozdaglar, Sarath Pattathil
2018	—	`conf`	Concentration bounds for two time scale stochastic approximation. Allerton Vivek S. Borkar, Sarath Pattathil
2018	J	`jnl`	Opportunistic Scheduling as Restless Bandits. IEEE Trans. Control. Netw. Syst. Vivek S. Borkar, Gaurav S. Kasbekar, Sarath Pattathil, Priyesh Y. Shetty
2018	B	`conf`	Persistence of the Jordan Center in Random Growing Trees. ASONAM Sarath Pattathil, Nikhil Karamchandani, Dhruti Shah
2017	—	`conf`	Controlling G-AIMD by index policy. CDC Konstantin E. Avrachenkov, Vivek S. Borkar, Sarath Pattathil
2017	J	`jnl`	Distributed Server Allocation for Content Delivery Networks. CoRR Sarath Pattathil, Vivek S. Borkar, Gaurav S. Kasbekar
2017	—	`conf`	Massive machine-type communication (mMTC) access with integrated authentication. ICC Nuno K. Pratas, Sarath Pattathil, Cedomir Stefanovic, Petar Popovski
2017	J	`jnl`	Opportunistic Scheduling as Restless Bandits. CoRR Vivek S. Borkar, Gaurav S. Kasbekar, Sarath Pattathil, Priyesh Y. Shetty
2017	B	`conf`	Optimal distributed scheduling for single-hop wireless networks. WiOpt Sarath Pattathil, Jayakrishnan Nair
2017	J	`jnl`	Persistence of the Jordan center in Random Growing Trees. CoRR Sarath Pattathil, Nikhil Karamchandani, Dhruti Shah
2017	J	`jnl`	Whittle Indexability in Egalitarian Processor Sharing Systems. CoRR Vivek S. Borkar, Sarath Pattathil
2016	J	`jnl`	Massive Machine-Type Communication (mMTC) Access with Integrated Authentication. CoRR Nuno K. Pratas, Sarath Pattathil, Cedomir Stefanovic, Petar Popovski