21 citations · 59 across the 20 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
Prescriptive Cluster-Dependent Support Vector Machines with an Application to Reducing Hospital Readmissions
Taiyao Wang, Ioannis Ch. Paschalidis
We augment linear Support Vector Machine (SVM) classifiers by adding three important features: (i) we introduce a regularization constraint to induce a sparse classifier; (ii) we d…
Convergence of Parameter Estimates for Regularized Mixed Linear Regression Models
Taiyao Wang, Ioannis Ch. Paschalidis
We consider {\em Mixed Linear Regression (MLR)}, where training data have been generated from a mixture of distinct linear models (or clusters) and we seek to identify the correspo…