no code implementations • 13 Feb 2023 • Xueying Liu, Shiaofen Fang, George Mohler, Joan Carlson, Yunyu Xiao
Recent data mining research has focused on the analysis of social media text, content and networks to identify suicide ideation online.
no code implementations • 21 Oct 2022 • Xenia Miscouridou, Samir Bhatt, George Mohler, Seth Flaxman, Swapnil Mishra
Here we develop a new class of spatiotemporal Hawkes processes that can capture both triggering and clustering behavior and we provide an efficient method for performing inference.
1 code implementation • NeurIPS 2021 • Sarkhan Badirli, Zeynep Akata, George Mohler, Christine Picard, Murat Dundar
Fine-grained zero-shot learning task requires some form of side-information to transfer discriminative information from seen to unseen classes.
1 code implementation • Springer US 2021 • Samira Khorshidi, Jeremy Carter, George Mohler, George Tita
Crime diversity is a measure of the variety of criminal offenses in a local environment, similar to ecological diversity.
1 code implementation • IEEE International Conference on Big Data (Big Data) 2020 • Samira Khorshidi, George Mohler, Jeremy G. Carter
We review several concepts and modeling techniques from statistical and machine learning that have been developed to forecast recidivism.
1 code implementation • 2020 IEEE International Conference on Intelligence and Security Informatics (ISI) 2020 • Samira Khorshidi, George Mohler, Jeremy G. Carter
Analysis and modeling of crime text report data has important applications, including refinement of crime classifications, clustering of documents, and feature extraction for spatio-temporal forecasts.
no code implementations • 12 Oct 2020 • Xueying Liu, Jeremy Carter, Brad Ray, George Mohler
We apply the algorithm to drug overdose data from Indianapolis, showing that the point process defined on the integrated data outperforms point processes that use only homogeneous EMS (AUC improvement . 72 to . 8) or coroner data (AUC improvement . 81 to . 85). We also investigate the extent to which overdoses are contagious, as a function of the type of overdose, while controlling for exogenous fluctuations in the background rate that might also contribute to clustering.
no code implementations • 3 Apr 2020 • Wen-Hao Chiang, George Mohler
We propose a novel framework for integrating Hawkes processes with multi-armed bandit algorithms to solve spatio-temporal event forecasting and detection problems when data may be undersampled or spatially biased.
no code implementations • 11 Mar 2019 • John Lu, Sumati Sridhar, Ritika Pandey, Mohammad Al Hasan, George Mohler
Increasing rates of opioid drug abuse and heightened prevalence of online support communities underscore the necessity of employing data mining techniques to better understand drug addiction using these rapidly developing online resources.
no code implementations • 8 Sep 2018 • Kathryn Gray, Daniel Smolyak, Sarkhan Badirli, George Mohler
In this paper we address two challenges that arise in the study of anomalous human trajectories: 1) a lack of ground truth data on what defines an anomaly and 2) the dependence of existing methods on significant pre-processing and feature engineering.
no code implementations • NeurIPS 2014 • George Mohler
In this paper we show how inverse covariance estimation can be dramatically improved using a simple convolution filter prior to applying sample covariance.