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20162026
most citedLocal Environment Poisoning Attacks on Federated Reinforcement Learning

5 citations · 15 across the 29 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

cs.GT2022

Distributed Computation for the Non-metric Data Placement Problem using Glauber Dynamics and Auctions

S. Rasoul Etesami

We consider the non-metric data placement problem and develop distributed algorithms for computing or approximating its optimal integral solution. We first show that the non-metric…

cs.SI2022

Limited-Trust in Diffusion of Competing Alternatives over Social Networks

Vincent Leon, S. Rasoul Etesami, Rakesh Nagi

We consider the diffusion of two alternatives in social networks using a game-theoretic approach. Each individual plays a coordination game with its neighbors repeatedly and decide…

cs.LG2022★ 3 cited

The Role of Local Steps in Local SGD

Tiancheng Qin, S. Rasoul Etesami, César A. Uribe

We consider the distributed stochastic optimization problem where agents want to minimize a global function given by the sum of agents' local functions, and focus on the hetero…

cs.IT2022

The Role of Gossiping for Information Dissemination over Networked Agents

Melih Bastopcu, S. Rasoul Etesami, Tamer Başar

We consider information dissemination over a network of gossiping agents (nodes). In this model, a source keeps the most up-to-date information about a time-varying binary state of…

cs.LG2022

Faster Convergence of Local SGD for Over-Parameterized Models

Tiancheng Qin, S. Rasoul Etesami, César A. Uribe

Modern machine learning architectures are often highly expressive. They are usually over-parameterized and can interpolate the data by driving the empirical loss close to zero. We…

cs.LG2022

Learning Stationary Nash Equilibrium Policies in -Player Stochastic Games with Independent Chains

S. Rasoul Etesami

We consider a subclass of -player stochastic games, in which players have their own internal state/action spaces while they are coupled through their payoff functions. It is ass…