George C. Runger

Orcid: 0000-0001-9460-6983

Affiliations:
  • Department of Industrial Engineering, Arizona State University


According to our database1, George C. Runger authored at least 58 papers between 1993 and 2024.

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Bibliography

2024
Attention-based Reinforcement Learning for Combinatorial Optimization: Application to Job Shop Scheduling Problem.
CoRR, 2024

2023
Dynamic Exploration-Exploitation Trade-Off in Active Learning Regression with Bayesian Hierarchical Modeling.
CoRR, 2023

2022
Addressing Fragmentation of Health Services through Data-Driven Knowledge Co-Production within a Boundary Organization.
J. Community Informatics, September, 2022

2021
MTBR: Multi-Target Boosting for Regression.
IEEE Trans. Knowl. Data Eng., 2021

Latinx Acculturation Scales: Scoping Review and Novel Scale Selection Tool.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020
Dynamic incorporation of prior knowledge from multiple domains in biomarker discovery.
BMC Bioinform., March, 2020

How Smartphone Accelerometers Reveal Aggressive Driving Behavior? - The Key is the Representation.
IEEE Trans. Intell. Transp. Syst., 2020

Matched Forest: supervised learning for high-dimensional matched case-control studies.
Bioinform., 2020

2019
Interpretable regularized class association rules algorithm for classification in a categorical data space.
Inf. Sci., 2019

Projection-free kernel principal component analysis for denoising.
Neurocomputing, 2019

2018
GCRNN: Group-Constrained Convolutional Recurrent Neural Network.
IEEE Trans. Neural Networks Learn. Syst., 2018

Distinct Variation Pattern Discovery Using Alternating Nonlinear Principal Component Analysis.
IEEE Trans. Neural Networks Learn. Syst., 2018

CRAFTER: A Tree-Ensemble Clustering Algorithm for Static Datasets with Mixed Attributes and High Dimensionality.
IEEE Trans. Knowl. Data Eng., 2018

Query-by-committee improvement with diversity and density in batch active learning.
Inf. Sci., 2018

2016
Discovering the Nature of Variation in Nonlinear Profile Data.
Technometrics, 2016

Time series representation and similarity based on local autopatterns.
Data Min. Knowl. Discov., 2016

2015
Learning a symbolic representation for multivariate time series classification.
Data Min. Knowl. Discov., 2015

2014
SMT: Sparse multivariate tree.
Stat. Anal. Data Min., 2014

Process Monitoring Using Hidden Markov Models.
Qual. Reliab. Eng. Int., 2014

Feature selection for noisy variation patterns using kernel principal component analysis.
Knowl. Based Syst., 2014

CBC: An associative classifier with a small number of rules.
Decis. Support Syst., 2014

2013
Gene selection with guided regularized random forest.
Pattern Recognit., 2013

A Bag-of-Features Framework to Classify Time Series.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

A time series forest for classification and feature extraction.
Inf. Sci., 2013

2012
Tangent Hyperplane Kernel Principal Component Analysis for Denoising.
IEEE Trans. Neural Networks Learn. Syst., 2012

Feature selection via regularized trees.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

2011
Learning Markov Blankets for Continuous or Discrete Networks via Feature Selection.
Proceedings of the Ensembles in Machine Learning Applications, 2011

Feature extraction and classification models for high-dimensional profile data.
Qual. Reliab. Eng. Int., 2011

Fault detection for batch monitoring and discrete wavelet transforms.
Qual. Reliab. Eng. Int., 2011

Active Batch Learning with Tree Ensembles.
Proceedings of the Active Learning and Experimental Design workshop, 2011

Extracting geographic knowledge from sensor intervention data using spatial association rules.
Proceedings of the IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, 2011

Target-aware Anomaly Detection and Diagnosis.
Proceedings of the ICINCO 2011 - Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics, Volume 1, Noordwijkerhout, The Netherlands, 28, 2011

Bias of Importance Measures for Multi-valued Attributes and Solutions.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

High-Dimensional Surveillance.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Image denoising with a multi-phase kernel principal component approach and an ensemble version.
Proceedings of the 2011 IEEE Applied Imagery Pattern Recognition Workshop: Imaging for Decision Making, 2011

2010
Time-based detection of changes to multivariate patterns.
Ann. Oper. Res., 2010

2009
A Novel Feature Selection Methodology for Automated Inspection Systems.
IEEE Trans. Pattern Anal. Mach. Intell., 2009

Feature Selection with Ensembles, Artificial Variables, and Redundancy Elimination.
J. Mach. Learn. Res., 2009

Integrative analysis of transcriptomic and proteomic data of <i>Desulfovibrio vulgaris</i>: a non-linear model to predict abundance of undetected proteins.
Bioinform., 2009

Zero-Inflated Boosted Ensembles for Rare Event Counts.
Proceedings of the Advances in Intelligent Data Analysis VIII, 2009

Contributor Diagnostics for Anomaly Detection.
Proceedings of the Artificial Neural Networks, 2009

Supervised multivariate discretization in mixed data with Random Forests.
Proceedings of the 7th IEEE/ACS International Conference on Computer Systems and Applications, 2009

2007
Using metarules to organize and group discovered association rules.
Data Min. Knowl. Discov., 2007

Change-point detection with supervised learning and feature selection.
Proceedings of the ICINCO 2007, 2007

2006
An Automated Feature Selection Method for Visual Inspection Systems.
IEEE Trans Autom. Sci. Eng., 2006

Relationships Among Control Charts Used with Feedback Control.
Qual. Reliab. Eng. Int., 2006

X-Ray Powder Diffraction Metrics.
Proceedings of the 2006 International Conference on Bioinformatics & Computational Biology, 2006

2005
Contributors to a signal from an artificial contrast.
Proceedings of the ICINCO 2005, 2005

2004
Adaptive server staffing in the presence of time-varying arrivals: a feed-forward control approach.
J. Oper. Res. Soc., 2004

Scoring Levels of Categorical Variables with Heterogeneous Data.
IEEE Intell. Syst., 2004

2003
Resampling methods for variable selection in robust regression.
Comput. Stat. Data Anal., 2003

Pre-Processing of High-Dimensional Categorical Predictors in Classification Settings.
Appl. Artif. Intell., 2003

2001
Assessment of operation plan performance under uncertainty.
IEEE Trans. Syst. Man Cybern. Syst., 2001

Using Experimental Design to Find Effective Parameter Settings for Heuristics.
J. Heuristics, 2001

2000
Plan performance assessment under uncertainty for command and control.
Proceedings of the ISCA 15th International Conference Computers and Their Applications, 2000

1998
See the forest before the trees: fine-tuned learning and its application to the traveling salesman problem.
IEEE Trans. Syst. Man Cybern. Part A, 1998

Neural network models for initial public offerings.
Neurocomputing, 1998

1993
The threshold bootstrap: a new approach to simulation output analysis.
Proceedings of the 25th Winter Simulation Conference, 1993


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