274 citations · 444 across the 26 of their papers we have counts for
7 papers · 1 filter
Distributed optimization on directed graphs based on inexact ADMM with partial participation
Dingran Yi, Nikolaos M. Freris
We consider the problem of minimizing the sum of cost functions pertaining to agents over a network whose topology is captured by a directed graph (i.e., asymmetric communication).…
Distributed Primal-dual Optimization for Heterogeneous Multi-agent Systems
Yichuan Li, Petros Voulgaris, Nikolaos M. Freris
Heterogeneous networks comprise agents with varying capabilities in terms of computation, storage, and communication. In such settings, it is crucial to factor in the operating cha…
FedADMM: A Robust Federated Deep Learning Framework with Adaptivity to System Heterogeneity
Yonghai Gong, Yichuan Li, Nikolaos M. Freris
Federated Learning (FL) is an emerging framework for distributed processing of large data volumes by edge devices subject to limited communication bandwidths, heterogeneity in data…
Communication Efficient Curvature Aided Primal-dual Algorithms for Decentralized Optimization
Yichuan Li, Petros G. Voulgaris, Dusan M. Stipanovic +1
This paper presents a family of algorithms for decentralized convex composite problems. We consider the setting of a network of agents that cooperatively minimize a global objectiv…
Dynamical Modeling and Control of Soft Robots with Non-constant Curvature Deformation
Zhanchi Wang, Gaotian Wang, Xiaoping Chen +1
The Piecewise Constant Curvature (PCC) model is the most widely used soft robotic modeling and control. However, the PCC fails to accurately describe the deformation of the soft ro…
A Communication Efficient Quasi-Newton Method for Large-scale Distributed Multi-agent Optimization
Yichuan Li, Petros G. Voulgaris, Nikolaos M. Freris
We propose a communication efficient quasi-Newton method for large-scale multi-agent convex composite optimization. We assume the setting of a network of agents that cooperatively…