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Herna L. Viktor
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Publications
- 2013
- [j12]Hongyu Guo, Herna L. Viktor, Eric Paquet:
Reducing the size of databases for multirelational classification: a subgraph-based approach. J. Intell. Inf. Syst. 40(2): 349-374 (2013) - 2012
- [c35]Michelangelo Ceci, Annalisa Appice, Herna L. Viktor, Donato Malerba, Eric Paquet, Hongyu Guo:
Transductive Relational Classification in the Co-training Paradigm. MLDM 2012: 11-25 - [c34]Eric Paquet, Herna Lydia Viktor, Hongyu Guo:
Learning in the Presence of Large Fluctuations: A Study of Aggregation and Correlation. NFMCP 2012: 49-63 - 2011
- [j10]Hongyu Guo, Herna L. Viktor, Eric Paquet:
Privacy Disclosure and Preservation in Learning with Multi-Relational Databases. J. Comput. Sci. Eng. 5(3): 183-196 (2011) - [c31]Hongyu Guo, Herna L. Viktor, Eric Paquet:
Privacy leakage in multi-relational learning via unwanted classification models. CASCON 2011: 45-59 - [c28]Eric Paquet, Herna L. Viktor, Hongyu Guo:
To Aggregate or Not to Aggregate: That is the Question. KDIR 2011: 354-357 - 2010
- [c24]Hongyu Guo, Herna L. Viktor, Eric Paquet:
Identifying and Preventing Data Leakage in Multi-relational Classification. ICDM Workshops 2010: 458-465 - 2008
- [j8]Hongyu Guo, Herna L. Viktor:
Learning from Skewed Class Multi-relational Databases. Fundam. Informaticae 89(1): 69-94 (2008) - [j7]Hongyu Guo, Herna L. Viktor:
Multirelational classification: a multiple view approach. Knowl. Inf. Syst. 17(3): 287-312 (2008) - 2007
- [c18]Hongyu Guo, Herna L. Viktor, Eric Paquet:
Pruning Relations for Substructure Discovery of Multi-relational Databases. PKDD 2007: 462-470 - 2006
- [c17]Hongyu Guo, Herna L. Viktor:
Multi-view ANNs for Multi-relational Classification. IJCNN 2006: 5259-5266 - [c16]Hongyu Guo, Herna L. Viktor:
Mining relational data through correlation-based multiple view validation. KDD 2006: 567-573 - [c15]Herna L. Viktor, Eric Paquet, Hongyu Guo:
Measuring to Fit: Virtual Tailoring Through Cluster Analysis and Classification. PKDD 2006: 395-406 - 2004
- [j3]Hongyu Guo, Herna L. Viktor:
Learning from imbalanced data sets with boosting and data generation: the DataBoost-IM approach. SIGKDD Explor. 6(1): 30-39 (2004) - [c14]Hongyu Guo, Herna L. Viktor:
Boosting with Data Generation: Improving the Classification of Hard to Learn Examples. IEA/AIE 2004: 1082-1091 - [c13]Herna L. Viktor, Hongyu Guo:
Multiple Classifier Prediction Improvements against Imbalanced Datasets through Added Synthetic Examples. SSPR/SPR 2004: 974-982
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