Eugene Tuv

28 papers A* 1B 2C 3Journal 8Unranked 9
YearRankTypeTitle / Venue / Authors
2014 J jnl
CBC: An associative classifier with a small number of rules.
Decis. Support Syst.
Houtao Deng, George C. Runger, Eugene Tuv, Wade Bannister
2013 J jnl
A Bag-of-Features Framework to Classify Time Series.
IEEE Trans. Pattern Anal. Mach. Intell.
Mustafa Gökçe Baydogan, George C. Runger, Eugene Tuv
2013 J jnl
A Time Series Forest for Classification and Feature Extraction
CoRR
Houtao Deng, George C. Runger, Eugene Tuv, Vladimir Martyanov
2013 J jnl
A time series forest for classification and feature extraction.
Inf. Sci.
Houtao Deng, George C. Runger, Eugene Tuv, Vladimir Martyanov
2011 — conf
Active Batch Learning with Tree Ensembles.
Active Learning and Experimental Design @ AISTATS
Alexander Borisov, Eugene Tuv, George C. Runger
2011 — conf
Bias of Importance Measures for Multi-valued Attributes and Solutions.
ICANN (2)
Houtao Deng, George C. Runger, Eugene Tuv
2011 — conf
High-Dimensional Surveillance.
ICANN (2)
Saylisse Dávila, George C. Runger, Eugene Tuv
2011 — ch.
Learning Markov Blankets for Continuous or Discrete Networks via Feature Selection.
Ensembles in Machine Learning Applications
Houtao Deng, Saylisse Dávila, George C. Runger, Eugene Tuv
2011 A* conf
Robust, Non-Redundant Feature Selection for Yield Analysis in Semiconductor Manufacturing.
ICDM
Éric St.-Pierre, Eugene Tuv
2011 — conf
Target-aware Anomaly Detection and Diagnosis.
ICINCO (1)
Alexander Borisov, George C. Runger, Eugene Tuv
2009 — conf
Contributor Diagnostics for Anomaly Detection.
ICANN (2)
Alexander Borisov, George C. Runger, Eugene Tuv
2009 J jnl
Feature Selection with Ensembles, Artificial Variables, and Redundancy Elimination.
J. Mach. Learn. Res.
Eugene Tuv, Alexander Borisov, George C. Runger, Kari Torkkola
2009 B conf
Zero-Inflated Boosted Ensembles for Rare Event Counts.
IDA
Alexander Borisov, George C. Runger, Eugene Tuv, Nuttha Lurponglukana-Strand
2008 — ch.
Ensembles of Least Squares Classifiers with Randomized Kernels.
Data Mining: Foundations and Practice
Kari Torkkola, Eugene Tuv
2007 — conf
Change-point detection with supervised learning and feature selection.
ICINCO-ICSO
Victor Eruhimov, Vladimir Martyanov, Eugene Tuv, George C. Runger
2007 — conf
Constructing High Dimensional Feature Space for Time Series Classification.
PKDD
Victor Eruhimov, Vladimir Martyanov, Eugene Tuv
2006 C conf
Best Subset Feature Selection for Massive Mixed-Type Problems.
IDEAL
Eugene Tuv, Alexander Borisov, Kari Torkkola
2006 C conf
Combining Unsupervised and Supervised Approaches to Feature Selection for Multivariate Signal Compression.
IDEAL
Victor Eruhimov, Vladimir Martyanov, Peter Raulefs, Eugene Tuv
2006 — ch.
Ensemble Learning.
Feature Extraction
Eugene Tuv
2006 — ch.
Ensembles of Regularized Least Squares Classifiers for High-Dimensional Problems.
Feature Extraction
Kari Torkkola, Eugene Tuv
2006 B conf
Feature Selection Using Ensemble Based Ranking Against Artificial Contrasts.
IJCNN
Eugene Tuv, Alexander Borisov, Kari Torkkola
2006 — conf
Supervised compression of multivariate time series data.
EUSIPCO
Victor Eruhimov, Vladimir Martyanov, Peter Raulefs, Eugene Tuv
2006 — ch.
Tree-Based Ensembles with Dynamic Soft Feature Selection.
Feature Extraction
Alexander Borisov, Victor Eruhimov, Eugene Tuv
2005 C conf
Contributors to a signal from an artificial contrast.
ICINCO
Jing Hu, George C. Runger, Eugene Tuv
2005 — conf
Ensemble Learning with Supervised Kernels.
ECML
Kari Torkkola, Eugene Tuv
2005 J jnl
Evolving Feature Selection.
IEEE Intell. Syst.
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
2004 J jnl
Scoring Levels of Categorical Variables with Heterogeneous Data.
IEEE Intell. Syst.
Eugene Tuv, George C. Runger
2003 J jnl
Pre-Processing of High-Dimensional Categorical Predictors in Classification Settings.
Appl. Artif. Intell.
Eugene Tuv, George C. Runger