21 citations · 59 across the 20 of their papers we have counts for
6 papers · 1 filter
Predicting Antimicrobial Resistance in the Intensive Care Unit
Taiyao Wang, Kyle R. Hansen, Joshua Loving +3
Antimicrobial resistance (AMR) is a risk for patients and a burden for the healthcare system. However, AMR assays typically take several days. This study develops predictive models…
Generalized Proximal Policy Optimization with Sample Reuse
James Queeney, Ioannis Ch. Paschalidis, Christos G. Cassandras
In real-world decision making tasks, it is critical for data-driven reinforcement learning methods to be both stable and sample efficient. On-policy methods typically generate reli…
Distributionally Robust Multi-Output Regression Ranking
Shahabeddin Sotudian, Ruidi Chen, Ioannis Paschalidis
Despite their empirical success, most existing listwiselearning-to-rank (LTR) models are not built to be robust to errors in labeling or annotation, distributional data shift, or a…
Distributionally Robust Learning
Ruidi Chen, Ioannis Ch. Paschalidis
This monograph develops a comprehensive statistical learning framework that is robust to (distributional) perturbations in the data using Distributionally Robust Optimization (DRO)…
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…
Communication-efficient SGD: From Local SGD to One-Shot Averaging
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…