The threshold bootstrap: a new approach to simulation output analysis. - Yun B. Kim; Thomas R. Willemain; Jorge Haddock; George C. Runger (WSC, 1993)

Neural network models for initial public offerings. - Steven J. Robertson; Bruce L. Golden; George C. Runger; Edward A. Wasil (Neurocomputing, 1998)

See the forest before the trees: fine-tuned learning and its application to the traveling salesman problem. - Steven P. Coy; Bruce L. Golden; George C. Runger; Edward A. Wasil (IEEE Trans. Syst. Man Cybern. Part A, 1998)

Plan performance assessment under uncertainty for command and control. - Nong Ye; Vuong Nguyen; George C. Runger (CATA, 2000)

Using Experimental Design to Find Effective Parameter Settings for Heuristics. - Steven P. Coy; Bruce L. Golden; George C. Runger; Edward A. Wasil (J. Heuristics, 2001)

Assessment of operation plan performance under uncertainty. - Nong Ye; Vuong Nguyen; George C. Runger (IEEE Trans. Syst. Man Cybern. Syst., 2001)

Pre-Processing of High-Dimensional Categorical Predictors in Classification Settings. - Eugene Tuv; George C. Runger (Appl. Artif. Intell., 2003)

Resampling methods for variable selection in robust regression. - James W. Wisnowski; James R. Simpson; Douglas C. Montgomery; George C. Runger (Comput. Stat. Data Anal., 2003)

Scoring Levels of Categorical Variables with Heterogeneous Data. - Eugene Tuv; George C. Runger (IEEE Intell. Syst., 2004)

Adaptive server staffing in the presence of time-varying arrivals: a feed-forward control approach. - Murat Caner Testik; Jeffery K. Cochran; George C. Runger (J. Oper. Res. Soc., 2004)

Contributors to a signal from an artificial contrast. - Jing Hu; George C. Runger; Eugene Tuv (ICINCO, 2005)

X-Ray Powder Diffraction Metrics. - George C. Runger; Kelly Canter; John Twist; David Rossi; Clifford Kirkham (BIOCOMP, 2006)

Relationships Among Control Charts Used with Feedback Control. - George Runger; Murat Caner Testik; Fugee Tsung (Qual. Reliab. Eng. Int., 2006)

An Automated Feature Selection Method for Visual Inspection Systems. - Hugo C. Garcia; Jesus René Villalobos; George C. Runger (IEEE Trans Autom. Sci. Eng., 2006)

Change-point detection with supervised learning and feature selection. - Victor Eruhimov; Vladimir Martyanov; Eugene Tuv; George C. Runger (ICINCO-ICSO, 2007)

Using metarules to organize and group discovered association rules. - Abdelaziz Berrado; George C. Runger (Data Min. Knowl. Discov., 2007)

Supervised multivariate discretization in mixed data with Random Forests. - Abdelaziz Berrado; George C. Runger (AICCSA, 2009)

Contributor Diagnostics for Anomaly Detection. - Alexander Borisov; George C. Runger; Eugene Tuv (ICANN (2), 2009)

Zero-Inflated Boosted Ensembles for Rare Event Counts. - Alexander Borisov; George C. Runger; Eugene Tuv; Nuttha Lurponglukana-Strand (IDA, 2009)

Integrative analysis of transcriptomic and proteomic data of Desulfovibrio vulgaris: a non-linear model to predict abundance of undetected proteins. - Wandaliz Torres-García; Weiwen Zhang; George C. Runger; Roger H. Johnson; Deirdre R. Meldrum (Bioinform., 2009)

Feature Selection with Ensembles, Artificial Variables, and Redundancy Elimination. - Eugene Tuv; Alexander Borisov; George C. Runger; Kari Torkkola (J. Mach. Learn. Res., 2009)

A Novel Feature Selection Methodology for Automated Inspection Systems. - Hugo C. Garcia; Jesus René Villalobos; Rong Pan; George C. Runger (IEEE Trans. Pattern Anal. Mach. Intell., 2009)

Time-based detection of changes to multivariate patterns. - Jing Hu; George C. Runger (Ann. Oper. Res., 2010)

Image denoising with a multi-phase kernel principal component approach and an ensemble version. - Anshuman Sahu; George C. Runger; Daniel W. Apley (AIPR, 2011)

High-Dimensional Surveillance. - Saylisse Dávila; George C. Runger; Eugene Tuv (ICANN (2), 2011)

Bias of Importance Measures for Multi-valued Attributes and Solutions. - Houtao Deng; George C. Runger; Eugene Tuv (ICANN (2), 2011)

Target-aware Anomaly Detection and Diagnosis. - Alexander Borisov; George C. Runger; Eugene Tuv (ICINCO (1), 2011)

Extracting geographic knowledge from sensor intervention data using spatial association rules. - Anirudh Kondaveeti; George C. Runger; Huan Liu 001; Jeremy Rowe (ICSDM, 2011)

Active Batch Learning with Tree Ensembles. - Alexander Borisov; Eugene Tuv; George C. Runger (Active Learning and Experimental Design @ AISTATS, 2011)

Fault detection for batch monitoring and discrete wavelet transforms. - Fang Li; George Church; Mani Janakiram; Howard Gholston; George C. Runger (Qual. Reliab. Eng. Int., 2011)

Feature extraction and classification models for high-dimensional profile data. - Amit Shinde; George Church; Mani Janakiram; George C. Runger (Qual. Reliab. Eng. Int., 2011)

Learning Markov Blankets for Continuous or Discrete Networks via Feature Selection. - Houtao Deng; Saylisse Dávila; George C. Runger; Eugene Tuv (Ensembles in Machine Learning Applications, 2011)

Feature selection via regularized trees. - Houtao Deng; George C. Runger (IJCNN, 2012)

Tangent Hyperplane Kernel Principal Component Analysis for Denoising. - Joon-Ku Im; Daniel W. Apley; George C. Runger (IEEE Trans. Neural Networks Learn. Syst., 2012)

A time series forest for classification and feature extraction. - Houtao Deng; George C. Runger; Eugene Tuv; Vladimir Martyanov (Inf. Sci., 2013)

A Bag-of-Features Framework to Classify Time Series. - Mustafa Gökçe Baydogan; George C. Runger; Eugene Tuv (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Gene selection with guided regularized random forest. - Houtao Deng; George C. Runger (Pattern Recognit., 2013)

CBC: An associative classifier with a small number of rules. - Houtao Deng; George C. Runger; Eugene Tuv; Wade Bannister (Decis. Support Syst., 2014)

Feature selection for noisy variation patterns using kernel principal component analysis. - Anshuman Sahu; Daniel W. Apley; George C. Runger (Knowl. Based Syst., 2014)

Process Monitoring Using Hidden Markov Models. - Hussam Alshraideh; George Runger (Qual. Reliab. Eng. Int., 2014)

SMT: Sparse multivariate tree. - Houtao Deng; Mustafa Gökçe Baydogan; George C. Runger (Stat. Anal. Data Min., 2014)

Learning a symbolic representation for multivariate time series classification. - Mustafa Gökçe Baydogan; George C. Runger (Data Min. Knowl. Discov., 2015)

Time series representation and similarity based on local autopatterns. - Mustafa Gökçe Baydogan; George C. Runger (Data Min. Knowl. Discov., 2016)

Discovering the Nature of Variation in Nonlinear Profile Data. - Zhenyu Shi; Daniel W. Apley; George C. Runger (Technometrics, 2016)

Query-by-committee improvement with diversity and density in batch active learning. - Seho Kee; Enrique del Castillo; George Runger (Inf. Sci., 2018)

CRAFTER: A Tree-Ensemble Clustering Algorithm for Static Datasets with Mixed Attributes and High Dimensionality. - Sangdi Lin; Bahareh Azarnoush; George C. Runger (IEEE Trans. Knowl. Data Eng., 2018)

Distinct Variation Pattern Discovery Using Alternating Nonlinear Principal Component Analysis. - Phillip Howard; Daniel W. Apley; George Runger (IEEE Trans. Neural Networks Learn. Syst., 2018)

GCRNN: Group-Constrained Convolutional Recurrent Neural Network. - Sangdi Lin; George C. Runger (IEEE Trans. Neural Networks Learn. Syst., 2018)

Projection-free kernel principal component analysis for denoising. - Anh Tuan Bui; Joon-Ku Im; Daniel W. Apley; George C. Runger (Neurocomputing, 2019)

Interpretable regularized class association rules algorithm for classification in a categorical data space. - Mohamed Azmi; George C. Runger; Abdelaziz Berrado (Inf. Sci., 2019)

Matched Forest: supervised learning for high-dimensional matched case-control studies. - Nooshin Shomal Zadeh; Sangdi Lin; George C. Runger (Bioinform., 2020)

How Smartphone Accelerometers Reveal Aggressive Driving Behavior? - The Key is the Representation. - Manuel Ricardo Carlos; Luis Carlos González-Gurrola; Johan Wahlström; Graciela Ramírez Alonso; Fernando Martínez 002; George Runger (IEEE Trans. Intell. Transp. Syst., 2020)

Dynamic incorporation of prior knowledge from multiple domains in biomarker discovery. - Xin Guan; George Runger; Li Liu (BMC Bioinform., 2020)

Latinx Acculturation Scales: Scoping Review and Novel Scale Selection Tool. - Anweysha Bhowmik; Logan Cameron; Julia Ivanova; Stanley Haynes; Ariana Cano; George Runger; Anita C. Murcko (AMIA, 2021)

MTBR: Multi-Target Boosting for Regression. - Sangdi Lin; Bahareh Azarnoush; George C. Runger (IEEE Trans. Knowl. Data Eng., 2021)

Addressing Fragmentation of Health Services through Data-Driven Knowledge Co-Production within a Boundary Organization. - Kathleen H. Pine; Margaret M. Hinrichs; Kailey Love; Michael Shafer; George Runger; William Riley (J. Community Informatics, 2022)

Dynamic Exploration-Exploitation Trade-Off in Active Learning Regression with Bayesian Hierarchical Modeling. - Upala Junaida Islam; Kamran Paynabar; George Runger; Ashif Sikandar Iquebal (CoRR, 2023)

Attention-based Reinforcement Learning for Combinatorial Optimization: Application to Job Shop Scheduling Problem. - Jaejin Lee; Seho Kee; Mani Janakiram; George Runger (CoRR, 2024)