Clustering Spatio-Temporal Waves of Covid-19
2023
A clustering methodology for studying geographic waves of infection evolving over time.
Authors: Kevin Quinn, Evimaria Terzi, Mark Crovella
2023
A clustering methodology for studying geographic waves of infection evolving over time.
Authors: Kevin Quinn, Evimaria Terzi, Mark Crovella
2024
In this paper we study fairness for multi-winner voting rules in a metric setting, focusing our attention on a novel definition we call group inefficiency to evaluate representation for select groups of voters.
Authors: Kevin Quinn, Moon Duchin
2025
Introduces partial interpretable clustering problem and algorithm, forgoing the requirement that every data point must be explained by the interpretable clustering model.
Authors: Kevin Quinn, Evimaria Terzi, Heikki Mannila
Published in ACM SIGKDD, 2022
We develop a framework for analyzing patterns of a disease or pandemic such as Covid using a new method of spatio-temporal decomposition called diffusion NMF (D-NMF).
Authors: Kevin Quinn, Evimaria Terzi, and Mark Crovella