George C. Runger

Publication Activity (10 Years)

Years Active: 1993-2021
Publications (10 Years): 8

Top Topics

Principal Component Analysis

Categorical Data

High Dimensional

Top Venues

IEEE Trans. Neural Networks Learn. Syst.

Data Min. Knowl. Discov.

IEEE Trans. Knowl. Data Eng.

Publications

Sangdi Lin, Bahareh Azarnoush, George C. Runger
MTBR: Multi-Target Boosting for Regression. IEEE Trans. Knowl. Data Eng. 33 (2) (2021)
Nooshin Shomal Zadeh, Sangdi Lin, George C. Runger
Matched Forest: supervised learning for high-dimensional matched case-control studies. Bioinform. 36 (5) (2020)
Mohamed Azmi, George C. Runger, Abdelaziz Berrado
Interpretable regularized class association rules algorithm for classification in a categorical data space. Inf. Sci. 483 (2019)
Anh Tuan Bui, Joon-Ku Im, Daniel W. Apley, George C. Runger
Projection-free kernel principal component analysis for denoising. Neurocomputing 357 (2019)
Sangdi Lin, Bahareh Azarnoush, George C. Runger
CRAFTER: A Tree-Ensemble Clustering Algorithm for Static Datasets with Mixed Attributes and High Dimensionality. IEEE Trans. Knowl. Data Eng. 30 (9) (2018)
Sangdi Lin, George C. Runger
GCRNN: Group-Constrained Convolutional Recurrent Neural Network. IEEE Trans. Neural Networks Learn. Syst. 29 (10) (2018)
Mustafa Gökçe Baydogan, George C. Runger
Time series representation and similarity based on local autopatterns. Data Min. Knowl. Discov. 30 (2) (2016)
Zhenyu Shi, Daniel W. Apley, George C. Runger
Discovering the Nature of Variation in Nonlinear Profile Data. Technometrics 58 (3) (2016)
Mustafa Gökçe Baydogan, George C. Runger
Learning a symbolic representation for multivariate time series classification. Data Min. Knowl. Discov. 29 (2) (2015)
Houtao Deng, Mustafa Gökçe Baydogan, George C. Runger
SMT: Sparse multivariate tree. Stat. Anal. Data Min. 7 (1) (2014)
Anshuman Sahu, Daniel W. Apley, George C. Runger
Feature selection for noisy variation patterns using kernel principal component analysis. Knowl. Based Syst. 72 (2014)
Houtao Deng, George C. Runger, Eugene Tuv, Wade Bannister
CBC: An associative classifier with a small number of rules. Decis. Support Syst. 59 (2014)
Houtao Deng, George C. Runger, Eugene Tuv, Vladimir Martyanov
A time series forest for classification and feature extraction. Inf. Sci. 239 (2013)
Mustafa Gökçe Baydogan, George C. Runger, Eugene Tuv
A Bag-of-Features Framework to Classify Time Series. IEEE Trans. Pattern Anal. Mach. Intell. 35 (11) (2013)
Houtao Deng, George C. Runger
Gene selection with guided regularized random forest. Pattern Recognit. 46 (12) (2013)
Houtao Deng, George C. Runger, Eugene Tuv, Vladimir Martyanov
A Time Series Forest for Classification and Feature Extraction CoRR (2013)
Houtao Deng, George C. Runger
Gene selection with guided regularized random forest CoRR (2012)
Joon-Ku Im, Daniel W. Apley, George C. Runger
Tangent Hyperplane Kernel Principal Component Analysis for Denoising. IEEE Trans. Neural Networks Learn. Syst. 23 (4) (2012)
Houtao Deng, George C. Runger
Feature selection via regularized trees. IJCNN (2012)
Houtao Deng, George C. Runger
Feature Selection via Regularized Trees CoRR (2012)
Alexander Borisov, Eugene Tuv, George C. Runger
Active Batch Learning with Tree Ensembles. Active Learning and Experimental Design @ AISTATS (2011)
Alexander Borisov, George C. Runger, Eugene Tuv
Target-aware Anomaly Detection and Diagnosis. ICINCO (1) (2011)
Amit Shinde, George Church, Mani Janakiram, George C. Runger
Feature extraction and classification models for high-dimensional profile data. Qual. Reliab. Eng. Int. 27 (7) (2011)
Fang Li, George Church, Mani Janakiram, Howard Gholston, George C. Runger
Fault detection for batch monitoring and discrete wavelet transforms. Qual. Reliab. Eng. Int. 27 (8) (2011)
Houtao Deng, George C. Runger, Eugene Tuv
Bias of Importance Measures for Multi-valued Attributes and Solutions. ICANN (2) (2011)
Saylisse Dávila, George C. Runger, Eugene Tuv
High-Dimensional Surveillance. ICANN (2) (2011)
Anirudh Kondaveeti, George C. Runger, Huan Liu, Jeremy Rowe
Extracting geographic knowledge from sensor intervention data using spatial association rules. ICSDM (2011)
Anshuman Sahu, George C. Runger, Daniel W. Apley
Image denoising with a multi-phase kernel principal component approach and an ensemble version. AIPR (2011)
Jing Hu, George C. Runger
Time-based detection of changes to multivariate patterns. Ann. Oper. Res. 174 (1) (2010)
Alexander Borisov, George C. Runger, Eugene Tuv, Nuttha Lurponglukana-Strand
Zero-Inflated Boosted Ensembles for Rare Event Counts. IDA (2009)
Hugo C. Garcia, Jesus René Villalobos, Rong Pan, George C. Runger
A Novel Feature Selection Methodology for Automated Inspection Systems. IEEE Trans. Pattern Anal. Mach. Intell. 31 (7) (2009)
Abdelaziz Berrado, George C. Runger
Supervised multivariate discretization in mixed data with Random Forests. AICCSA (2009)
Wandaliz Torres-García, Weiwen Zhang, George C. Runger, Roger H. Johnson, Deirdre R. Meldrum
: a non-linear model to predict abundance of undetected proteins. Bioinform. 25 (15) (2009)
Alexander Borisov, George C. Runger, Eugene Tuv
Contributor Diagnostics for Anomaly Detection. ICANN (2) (2009)
Eugene Tuv, Alexander Borisov, George C. Runger, Kari Torkkola
Feature Selection with Ensembles, Artificial Variables, and Redundancy Elimination. J. Mach. Learn. Res. 10 (2009)
Victor Eruhimov, Vladimir Martyanov, Eugene Tuv, George C. Runger
Change-point detection with supervised learning and feature selection. ICINCO-ICSO (2007)
Abdelaziz Berrado, George C. Runger
Using metarules to organize and group discovered association rules. Data Min. Knowl. Discov. 14 (3) (2007)
George C. Runger, Kelly Canter, John Twist, David Rossi, Clifford Kirkham
X-Ray Powder Diffraction Metrics. BIOCOMP (2006)
Hugo C. Garcia, Jesus René Villalobos, George C. Runger
An Automated Feature Selection Method for Visual Inspection Systems. IEEE Trans Autom. Sci. Eng. 3 (4) (2006)
Jing Hu, George C. Runger, Eugene Tuv
Contributors to a signal from an artificial contrast. ICINCO (2005)
Murat Caner Testik, Jeffery K. Cochran, George C. Runger
Adaptive server staffing in the presence of time-varying arrivals: a feed-forward control approach. J. Oper. Res. Soc. 55 (3) (2004)
Eugene Tuv, George C. Runger
Scoring Levels of Categorical Variables with Heterogeneous Data. IEEE Intell. Syst. 19 (2) (2004)
James W. Wisnowski, James R. Simpson, Douglas C. Montgomery, George C. Runger
Resampling methods for variable selection in robust regression. Comput. Stat. Data Anal. 43 (3) (2003)
Eugene Tuv, George C. Runger
Pre-Processing of High-Dimensional Categorical Predictors in Classification Settings. Appl. Artif. Intell. 17 (5-6) (2003)
Steven P. Coy, Bruce L. Golden, George C. Runger, Edward A. Wasil
Using Experimental Design to Find Effective Parameter Settings for Heuristics. J. Heuristics 7 (1) (2001)
Nong Ye, Vuong Nguyen, George C. Runger
Assessment of operation plan performance under uncertainty. IEEE Trans. Syst. Man Cybern. Syst. 31 (2) (2001)
Nong Ye, Vuong Nguyen, George C. Runger
Plan performance assessment under uncertainty for command and control. CATA (2000)
Steven J. Robertson, Bruce L. Golden, George C. Runger, Edward A. Wasil
Neural network models for initial public offerings. Neurocomputing 18 (1-3) (1998)
Steven P. Coy, Bruce L. Golden, George C. Runger, Edward A. Wasil
See the forest before the trees: fine-tuned learning and its application to the traveling salesman problem. IEEE Trans. Syst. Man Cybern. Part A 28 (4) (1998)
Yun B. Kim, Thomas R. Willemain, Jorge Haddock, George C. Runger
The threshold bootstrap: a new approach to simulation output analysis. WSC (1993)