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Dive into the research topics where Kyle Miller is active.

Publication


Featured researches published by Kyle Miller.


Journal of Human Trafficking | 2015

Leveraging Publicly Available Data to Discern Patterns of Human-Trafficking Activity

Artur Dubrawski; Kyle Miller; Matt Barnes; Benedikt Boecking; Emily Kennedy

We present a few data analysis methods that can be used to process advertisements for escort services available in public areas of the Internet. These data provide a readily available proxy evidence for modeling and discerning human-trafficking activity. We show how it can be used to identify advertisements that likely involve such activity. We demonstrate its utility in identifying and tracking entities in the Web-advertisement data even if strongly identifiable features are sparse. We also show a few possible ways to perform community- and population-level analyses including behavioral summaries stratified by various types of activity and detection of emerging trends and patterns.


Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment | 2016

Evaluation of coded aperture radiation detectors using a Bayesian approach

Kyle Miller; Peter Huggins; Simon E. Labov; Karl Nelson; Artur Dubrawski

We investigate tradeoffs arising from the use of coded aperture gamma-ray spectrometry to detect and localize sources of harmful radiation in the presence of noisy background. Using an example application scenario of area monitoring and search, we empirically evaluate weakly supervised spectral, spatial, and hybrid spatio-spectral algorithms for scoring individual observations, and two alternative methods of fusing evidence obtained from multiple observations. Results of our experiments confirm the intuition that directional information provided by spectrometers masked with coded aperture enables gains in source localization accuracy, but at the expense of reduced probability of detection. Losses in detection performance can however be to a substantial extent reclaimed by using our new spatial and spatio-spectral scoring methods which rely on realistic assumptions regarding masking and its impact on measured photon distributions.


Journal of Human Trafficking | 2018

Quantifying the Relationship between Large Public Events and Escort Advertising Behavior

Benedikt Boecking; Kyle Miller; Emily Kennedy; Artur Dubrawski

ABSTRACT We study online escort advertisement responses to large scale public events using a time series anomaly detection framework. We analyze advertisement volume, approximations of advertiser volumes, and further devise a measure for movement derived from the spatio-temporal behavior amongst related advertisements. Our results imply that a variety of events correlate with unusual increases in sex worker activity, including an influx of providers that are new to the respective event location. The findings indicate that there are strong market responses to some public events and that Super Bowl events which received heightened attention by authorities and news media due to a perceived link to human trafficking for sexual exploitation do not stand out amongst these events in the effect on the market that we measured.


empirical methods in natural language processing | 2017

An Entity Resolution approach to isolate instances of Human Trafficking online

Chirag Nagpal; Kyle Miller; Benedikt Boecking; Artur Dubrawski


arXiv: Applications | 2016

Do Public Events Affect Sex Trafficking Activity

Kyle Miller; Emily Kennedy; Artur Dubrawski


IEEE Transactions on Nuclear Science | 2018

Gamma-Ray Source Detection With Small Sensors

Kyle Miller; Artur Dubrawski


neural information processing systems | 2017

Noise-Tolerant Interactive Learning Using Pairwise Comparisons

Yichong Xu; Hongyang Zhang; Kyle Miller; Aarti Singh; Artur Dubrawski


international conference on data mining | 2017

Semi-Supervised Prediction of Comorbid Rare Conditions Using Medical Claims Data

Chirag Nagpal; Kyle Miller; Tiffany Pellathy; Marilyn Hravnak; Gilles Clermont; Michael R. Pinsky; Artur Dubrawski


Archive | 2017

Noise-Tolerant Interactive Learning from Pairwise Comparisons with Near-Minimal Label Complexity

Yichong Xu; Hongyang Zhang; Kyle Miller; Aarti Singh; Artur Dubrawski


Archive | 2017

Learning Mixtures of Multi-Output Regression Models by Correlation Clustering for Multi-View Data.

Eric Lei; Kyle Miller; Artur Dubrawski

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Artur Dubrawski

Carnegie Mellon University

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Benedikt Boecking

Carnegie Mellon University

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Emily Kennedy

Carnegie Mellon University

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Aarti Singh

Carnegie Mellon University

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Matt Barnes

Carnegie Mellon University

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Yichong Xu

Carnegie Mellon University

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Karl Nelson

Lawrence Livermore National Laboratory

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