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20132022
most citedDSA: Decentralized Double Stochastic Averaging Gradient Algorithm

146 citations · 176 across the 17 of their papers we have counts for

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Showing 2019Show all

10 papers · 1 filter

eess.SP2019

Optimal Wireless Resource Allocation with Random Edge Graph Neural Networks

Mark Eisen, Alejandro Ribeiro

We consider the problem of optimally allocating resources across a set of transmitters and receivers in a wireless network. The resulting optimization problem takes the form of con…

cs.RO2019

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints

Arbaaz Khan, Chi Zhang, Shuo Li +6

In this paper, we present a learning approach to goal assignment and trajectory planning for unlabeled robots operating in 2D, obstacle-filled workspaces. More specifically, we tac…

cs.RO2019

Graph Policy Gradients for Large Scale Robot Control

Arbaaz Khan, Ekaterina Tolstaya, Alejandro Ribeiro +1

In this paper, we consider the problem of learning policies to control a large number of homogeneous robots. To this end, we propose a new algorithm we call Graph Policy Gradients…

eess.SP2019

Optimal WDM Power Allocation via Deep Learning for Radio on Free Space Optics Systems

Zhan Gao, Mark Eisen, Alejandro Ribeiro

Radio on Free Space Optics (RoFSO), as a universal platform for heterogeneous wireless services, is able to transmit multiple radio frequency signals at high rates in free space op…

eess.SP2019

Control-Aware Scheduling for Low Latency Wireless Systems with Deep Learning

Mark Eisen, Mohammad M. Rashid, Dave Cavalcanti +1

We consider the problem of scheduling transmissions over low-latency wireless communication links to control various control systems. Low-latency requirements are critical in devel…

cs.RO2019

Inverse Optimal Planning for Air Traffic Control

Ekaterina Tolstaya, Alejandro Ribeiro, Vijay Kumar +1

We envision a system that concisely describes the rules of air traffic control, assists human operators and supports dense autonomous air traffic around commercial airports. We dev…