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20152021
most citedGeneralized Proximal Policy Optimization with Sample Reuse

21 citations · 59 across the 14 of their papers we have counts for

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9 papers · 1 filter

math.OC2021

Planning Strategies for Lane Reversals in Transportation Networks

Salomon Wollenstein-Betech, Ioannis Ch. Paschalidis, Christos G. Cassandras

This paper studies strategies to optimize the lane configuration of a transportation network for a given set of Origin-Destination demands using a planning macroscopic network flow…

math.OC202012 cited

Local SGD With a Communication Overhead Depending Only on the Number of Workers

Artin Spiridonoff, Alex Olshevsky, Ioannis Ch. Paschalidis

We consider speeding up stochastic gradient descent (SGD) by parallelizing it across multiple workers. We assume the same data set is shared among workers, who can take SGD ste…

math.OC2020

Joint Pricing and Rebalancing of Autonomous Mobility-on-Demand Systems

Salomón Wollenstein-Betech, Ioannis Ch. Paschalidis, Christos G. Cassandras

This paper studies optimal pricing and rebalancing policies for Autonomous Mobility-on-Demand (AMoD) systems. We take a macroscopic planning perspective to tackle a profit maximiza…

math.OC2019

Joint Estimation of OD Demands and Cost Functions in Transportation Networks from Data

Salomón Wollenstein-Betech, Chuangchuang Sun, Jing Zhang +1

Existing work has tackled the problem of estimating Origin-Destination (OD) demands and recovering travel latency functions in transportation networks under the Wardropian assumpti…

math.OC2019

Asymptotic Network Independence in Distributed Stochastic Optimization for Machine Learning

Shi Pu, Alex Olshevsky, Ioannis Ch. Paschalidis

We provide a discussion of several recent results which, in certain scenarios, are able to overcome a barrier in distributed stochastic optimization for machine learning. Our focus…

math.OC2019

A Sharp Estimate on the Transient Time of Distributed Stochastic Gradient Descent

Shi Pu, Alex Olshevsky, Ioannis Ch. Paschalidis

This paper is concerned with minimizing the average of cost functions over a network in which agents may communicate and exchange information with each other. We consider the s…