activity
20172021
most citedOne-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them

18 citations · 32 across the 8 of their papers we have counts for

collaborators

9 papers

cs.LG2021★ 1 cited

Order Optimal Bounds for One-Shot Federated Learning over non-Convex Loss Functions

Arsalan Sharifnassab, Saber Salehkaleybar, S. Jamaloddin Golestani

We consider the problem of federated learning in a one-shot setting in which there are machines, each observing sample functions from an unknown distribution on non-convex…

cs.MA2021★ 1 cited

Distributed Fair Scheduling for Information Exchange in Multi-Agent Systems

Majid Raeis, S. Jamaloddin Golestani

Information exchange is a crucial component of many real-world multi-agent systems. However, the communication between the agents involves two major challenges: the limited bandwid…

cs.LG2019★ 4 cited

Order Optimal One-Shot Distributed Learning

Arsalan Sharifnassab, Saber Salehkaleybar, S. Jamaloddin Golestani

We consider distributed statistical optimization in one-shot setting, where there are machines each observing i.i.d. samples. Based on its observed samples, each machine th…

eess.SY2019★ 1 cited

Nonexpansive Piecewise Constant Hybrid Systems are Conservative

Arsalan Sharifnassab, John N. Tsitsiklis, S. Jamaloddin Golestani

Consider a partition of into finitely many polyhedral regions and associated drift vectors . We study ``hybrid'' dynamical systems whose trajectories have a…

eess.SY2019

When do Trajectories have Bounded Sensitivity to Cumulative Perturbations?

Arsalan Sharifnassab, S. Jamaloddin Golestani

We investigate sensitivity to cumulative perturbations for a few dynamical system classes of practical interest. A system is said to have bounded sensitivity to cumulative perturba…

cs.LG2019★ 18 cited

One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them

Saber Salehkaleybar, Arsalan Sharifnassab, S. Jamaloddin Golestani

We consider distributed statistical optimization in one-shot setting, where there are machines each observing i.i.d. samples. Based on its observed samples, each machine se…

cs.NI2018

Fluctuation Bounds for the Max-Weight Policy, with Applications to State Space Collapse

Arsalan Sharifnassab, John N. Tsitsiklis, S. Jamaloddin Golestani

We consider a multi-hop switched network operating under a Max-Weight (MW) scheduling policy, and show that the distance between the queue length process and a fluid solution remai…

eess.SY2018

Sensitivity to Cumulative Perturbations for a Class of Piecewise Constant Hybrid Systems

Arsalan Sharifnassab, John N. Tsitsiklis, Jamaloddin Golestani

We consider a class of continuous-time hybrid dynamical systems that correspond to subgradient flows of a piecewise linear and convex potential function with finitely many pieces,…

cs.IT2017★ 7 cited

On the relaxed maximum-likelihood blind MIMO channel estimation for orthogonal space-time block codes

Kamran Kalbasi, S. Jamaloddin Golestani

This paper concerns the maximum-likelihood channel estimation for MIMO systems with orthogonal space-time block codes when the finite alphabet constraint of the signal constellatio…