William Herlands


Machine Learning for Drug Overdose Surveillance
Daniel B. Neill and William Herlands
Data for Good Exchange (D4GX), 2017
Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces
William Herlands, Andrew Gordon Wilson, Hannes Nickisch, Seth Flaxman, Daniel B. Neill, Wilbert van Panhuis, and Eric Xing
Artificial Intelligence and Statistics (AISTATS), 2016
[PDF, supplement, arXiv, BibTeX]
Lass-zero: Sparse Non-Convex Regression by Local Search
William Herlands, Maria De-Arteaga, Daniel B. Neill, and Artur Dubrawski
NIPS Workshop on Optimization, 2015
[PDF, arXiv, BibTeX]
A Machine Learning Approach to Musically Meaningful Homogeneous Style Classification
William Herlands, Ricky Der, Yoel Greenberg, and Simon Levin
Association for the Advancement in Artificial Intelligence (AAAI), 2014
[PDF, BibTeX]
Effective Entropy: Security-Centric Metric for Memory Randomization Technologies
William Herlands, Thomas Hobson, and Paula J. Donovan
USENIX Workshop on Cybersecurity Security Experimentation, 2014
[PDF, BibTeX]
Intelligent Sensor Interconnection Networks Performing Signal Classification
William Herlands, Mable Fok, and Paul Prucnal
IEEE Conference on Photonic Interconnections with High Speed Digital Systems, 2011


Generalized Difference in Difference Models with Gaussian Processes
Joint Statistical Meetings. Chicago, Illinois 08/2016
Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces
Heinz College First Paper presentation, CMU. Pittsburgh, PA 05/2016
Small Area Spatiotemporal Crime Rate Forecasting
The American Society of Criminology. Washington D.C. 11/2015