Eugene Tuv

Publication Activity (10 Years)

Years Active: 2003-2014
Publications (10 Years): 0

Top Topics

Associative Classification

Statistical Pattern Recognition

Smoke Detection

Feature Extraction

Top Venues

Decis. Support Syst.

IEEE Trans. Pattern Anal. Mach. Intell.

Publications

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, Eugene Tuv, Vladimir Martyanov
A Time Series Forest for Classification and Feature Extraction CoRR (2013)
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)
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)
Éric St.-Pierre, Eugene Tuv
Robust, Non-Redundant Feature Selection for Yield Analysis in Semiconductor Manufacturing. ICDM (2011)
Alexander Borisov, George C. Runger, Eugene Tuv, Nuttha Lurponglukana-Strand
Zero-Inflated Boosted Ensembles for Rare Event Counts. IDA (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)
Victor Eruhimov, Vladimir Martyanov, Eugene Tuv
Constructing High Dimensional Feature Space for Time Series Classification. PKDD (2007)
Victor Eruhimov, Vladimir Martyanov, Peter Raulefs, Eugene Tuv
Combining Unsupervised and Supervised Approaches to Feature Selection for Multivariate Signal Compression. IDEAL (2006)
Eugene Tuv, Alexander Borisov, Kari Torkkola
Best Subset Feature Selection for Massive Mixed-Type Problems. IDEAL (2006)
Eugene Tuv, Alexander Borisov, Kari Torkkola
Feature Selection Using Ensemble Based Ranking Against Artificial Contrasts. IJCNN (2006)
Victor Eruhimov, Vladimir Martyanov, Peter Raulefs, Eugene Tuv
Supervised compression of multivariate time series data. EUSIPCO (2006)
Kari Torkkola, Eugene Tuv
Ensemble Learning with Supervised Kernels. ECML (2005)
Jing Hu, George C. Runger, Eugene Tuv
Contributors to a signal from an artificial contrast. ICINCO (2005)
Huan Liu, Edward R. Dougherty, Jennifer G. Dy, Kari Torkkola, Eugene Tuv, Hanchuan Peng, Chris H. Q. Ding, Fuhui Long, Michael E. Berens, Lance Parsons, Zheng Zhao, Lei Yu, George Forman
Evolving Feature Selection. IEEE Intell. Syst. 20 (6) (2005)
Eugene Tuv, George C. Runger
Scoring Levels of Categorical Variables with Heterogeneous Data. IEEE Intell. Syst. 19 (2) (2004)
Eugene Tuv, George C. Runger
Pre-Processing of High-Dimensional Categorical Predictors in Classification Settings. Appl. Artif. Intell. 17 (5-6) (2003)