Daniel B. Neill

According to our database, Daniel B. Neill authored at least 55 papers between 2003 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Efficient Optimization of Partition Scan Statistics via the Consecutive Partitions Property.

Charles A. Pehlivanian, Daniel B. Neill

J. Comput. Graph. Stat., April, 2023

Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators.

Benjamin Jakubowski, Sriram Somanchi, Edward McFowland III, Daniel B. Neill

J. Mach. Learn. Res., 2023

Auditing Predictive Models for Intersectional Biases.

Kate S. Boxer, Edward McFowland III, Daniel B. Neill

CoRR, 2023

Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness.

Neil Menghani, Edward McFowland III, Daniel B. Neill

CoRR, 2023

Positional Encoder Graph Neural Networks for Geographic Data.

Konstantin Klemmer, Nathan S. Safir, Daniel B. Neill

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Detecting Anomalous Networks of Opioid Prescribers and Dispensers in Prescription Drug Data.

Katie Rosman, Daniel B. Neill

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Provable Detection of Propagating Sampling Bias in Prediction Models.

Pavan Ravishankar, Qingyu Mo, Edward McFowland III, Daniel B. Neill

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Calibrated Nonparametric Scan Statistics for Anomalous Pattern Detection in Graphs.

Chunpai Wang, Daniel B. Neill, Feng Chen

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

SPATE-GAN: Improved Generative Modeling of Dynamic Spatio-Temporal Patterns with an Autoregressive Embedding Loss.

Konstantin Klemmer, Tianlin Xu, Beatrice Acciaio, Daniel B. Neill

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Support vector subset scan for spatial pattern detection.

Dylan J. Fitzpatrick, Yun Ni, Daniel B. Neill

Comput. Stat. Data Anal., 2021

Auxiliary-task learning for geographic data with autoregressive embeddings.

Konstantin Klemmer, Daniel B. Neill

Proceedings of the SIGSPATIAL '21: 29th International Conference on Advances in Geographic Information Systems, 2021

Automatic Stratification of Tabular Health Data.

Skyler Speakman, Girmaw Abebe Tadesse, Victor Akinwande, William Ogallo, Claire-Helene Mershon, Nosa Orobaton, Daniel B. Neill

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020

Guest Editorial: Special Issue on Analytics for Local Events and News.

Amr Magdy, Xun Zhou, Daniel B. Neill

GeoInformatica, 2020

Policing Chronic and Temporary Hot Spots of Violent Crime: A Controlled Field Experiment.

Dylan J. Fitzpatrick, Wilpen L. Gorr, Daniel B. Neill

CoRR, 2020

SXL: Spatially explicit learning of geographic processes with auxiliary tasks.

Konstantin Klemmer, Daniel B. Neill

CoRR, 2020

2019

Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction.

William Herlands, Daniel B. Neill, Hannes Nickisch, Andrew Gordon Wilson

J. Mach. Learn. Res., 2019

Detecting Spatial Clusters of Disease Infection Risk Using Sparsely Sampled Social Media Mobility Patterns.

Roberto C. S. N. P. Souza, Renato M. Assunção, Daniel B. Neill, Wagner Meira Jr.

Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019

2018

Disease Surveillance: Case Study.

Skyler Speakman, Sriram Somanchi, Edward McFowland III, Daniel B. Neill

Proceedings of the Encyclopedia of Social Network Analysis and Mining, 2nd Edition, 2018

Machine Learning for the Developing World.

Maria De-Arteaga, William Herlands, Daniel B. Neill, Artur Dubrawski

ACM Trans. Manag. Inf. Syst., 2018

Modeling Rape Reporting Delays Using Spatial, Temporal and Social Features.

Konstantin Klemmer, Daniel B. Neill, Stephen A. Jarvis

CoRR, 2018

Automated Local Regression Discontinuity Design Discovery.

William Herlands, Edward McFowland III, Andrew Gordon Wilson, Daniel B. Neill

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data.

William Herlands, Edward McFowland, Andrew Gordon Wilson, Daniel B. Neill

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Subset Scanning for Event and Pattern Detection.

Daniel B. Neill

Proceedings of the Encyclopedia of GIS., 2017

Graph Structure Learning from Unlabeled Data for Early Outbreak Detection.

Sriram Somanchi, Daniel B. Neill

IEEE Intell. Syst., 2017

Machine Learning for Drug Overdose Surveillance.

Daniel B. Neill, William Herlands

CoRR, 2017

Graph Structure Learning from Unlabeled Data for Event Detection.

Sriram Somanchi, Daniel B. Neill

CoRR, 2017

2016

Gaussian Processes for Independence Tests with Non-iid Data in Causal Inference.

Seth R. Flaxman, Daniel B. Neill, Alexander J. Smola

ACM Trans. Intell. Syst. Technol., 2016

Identifying Significant Predictive Bias in Classifiers.

Zhe Zhang, Daniel B. Neill

CoRR, 2016

Semantic Scan: Detecting Subtle, Spatially Localized Events in Text Streams.

Abhinav Maurya, Kenton Murray, Yandong Liu, Chris Dyer, William W. Cohen, Daniel B. Neill

CoRR, 2016

Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces.

William Herlands, Andrew Gordon Wilson, Hannes Nickisch, Seth R. Flaxman, Daniel B. Neill, Wilbert Van Panhuis, Eric P. Xing

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Machine Learning Approaches for Early DRG Classification and Resource Allocation.

Daniel Gartner, Rainer Kolisch, Daniel B. Neill, Rema Padman

INFORMS J. Comput., 2015

Human Rights Event Detection from Heterogeneous Social Media Graphs.

Feng Chen, Daniel B. Neill

Big Data, 2015

Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods.

Seth R. Flaxman, Andrew Gordon Wilson, Daniel B. Neill, Hannes Nickisch, Alexander J. Smola

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Disease Surveillance, Case Study.

Skyler Speakman, Sriram Somanchi, Edward McFowland, Daniel B. Neill

Encyclopedia of Social Network Analysis and Mining, 2014

Non-parametric scan statistics for event detection and forecasting in heterogeneous social media graphs.

Feng Chen, Daniel B. Neill

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

2013

Fast generalized subset scan for anomalous pattern detection.

Edward McFowland, Skyler Speakman, Daniel B. Neill

J. Mach. Learn. Res., 2013

Using Artificial Intelligence to Improve Hospital Inpatient Care.

Daniel B. Neill

IEEE Intell. Syst., 2013

Dynamic Pattern Detection with Temporal Consistency and Connectivity Constraints.

Skyler Speakman, Yating Zhang, Daniel B. Neill

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012

New Directions in Artificial Intelligence for Public Health Surveillance.

Daniel B. Neill

IEEE Intell. Syst., 2012

Information Visualization for Chronic Disease Risk Assessment.

Christopher A. Harle, Daniel B. Neill, Rema Padman

IEEE Intell. Syst., 2012

2011

Detection of Patterns in Water Distribution Pipe Breakage Using Spatial Scan Statistics for Point Events in a Physical Network.

Daniel P. de Oliveira, Daniel B. Neill, James H. Garrett Jr., Lucio Soibelman

J. Comput. Civ. Eng., 2011

Automatic detection of omissions in medication lists.

Sharique Hasan, George T. Duncan, Daniel B. Neill, Rema Padman

J. Am. Medical Informatics Assoc., 2011

A Generalized Fast Subset Sums Framework for Bayesian Event Detection.

Kan Shao, Yandong Liu, Daniel B. Neill

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2010

A multivariate Bayesian scan statistic for early event detection and characterization.

Daniel B. Neill, Gregory F. Cooper

Mach. Learn., 2010

A Bayesian network model for spatial event surveillance.

Xia Jiang, Daniel B. Neill, Gregory F. Cooper

Int. J. Approx. Reason., 2010

2009

T-Cube Web Interface in support of real-time bio-surveillance program.

Artur Dubrawski, Maheshkumar Sabhnani, Michael Knight, Michael Baysek, Daniel B. Neill, Saswati Ray, Anna Michalska, Nuwan Waidyanatha

Proceedings of the 2009 International Conference on Information and Communication Technologies and Development, 2009

Generalized AMOC Curves For Evaluation and Improvement of Event Surveillance.

Xia Jiang, Gregory F. Cooper, Daniel B. Neill

Proceedings of the AMIA 2009, 2009

2008

Anomaly pattern detection in categorical datasets.

Kaustav Das, Jeff G. Schneider, Daniel B. Neill

Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Towards a Collaborative Filtering Approach to Medication Reconciliation.

Sharique Hasan, George T. Duncan, Daniel B. Neill, Rema Padman

Proceedings of the AMIA 2008, 2008

2005

A Bayesian Spatial Scan Statistic.

Daniel B. Neill, Andrew W. Moore, Gregory F. Cooper

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Detection of emerging space-time clusters.

Daniel B. Neill, Andrew W. Moore, Maheshkumar Sabhnani, Kenny Daniel

Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2005

2004

Detecting Significant Multidimensional Spatial Clusters.

Daniel B. Neill, Andrew W. Moore, Francisco Pereira, Tom M. Mitchell

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Rapid detection of significant spatial clusters.

Daniel B. Neill, Andrew W. Moore

Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

2003

Cooperation and coordination in the turn-taking dilemma.

Daniel B. Neill

Proceedings of the 9th Conference on Theoretical Aspects of Rationality and Knowledge (TARK-2003), 2003

A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters.

Daniel B. Neill, Andrew W. Moore

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003