Vladimir Cherkassky
Affiliations: | Electrical Engineering | University of Minnesota, Twin Cities, Minneapolis, MN |
Area:
Electronics and Electrical Engineering, Computer ScienceGoogle:
"Vladimir Cherkassky"Children
Sign in to add trainee| Yunqian Ma | grad student | 2003 | UMN |
| Lichen Liang | grad student | 2007 | UMN |
| Tao Xiong | grad student | 2007 | UMN |
| Feng Cai | grad student | 2011 | UMN |
| Sauptik Dhar | grad student | 2014 | UMN |
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Publications
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| Cherkassky V, Lee EH. (2023) To understand double descent, we need to understand VC theory. Neural Networks : the Official Journal of the International Neural Network Society. 169: 242-256 |
| Chen HH, Cherkassky V. (2020) Performance metrics for online seizure prediction. Neural Networks : the Official Journal of the International Neural Network Society. 128: 22-32 |
| Dhar S, Cherkassky V. (2015) Development and evaluation of cost-sensitive universum-SVM. Ieee Transactions On Cybernetics. 45: 806-18 |
| Cherkassky V, Dhar S. (2015) Interpretation of black-box predictive models Measures of Complexity: Festschrift For Alexey Chervonenkis. 267-286 |
| Shiao HT, Cherkassky V. (2014) Learning using privileged information (LUPI) for modeling survival data Proceedings of the International Joint Conference On Neural Networks. 1042-1049 |
| Sivasankaran A, Madbouly A, Cherkassky V, et al. (2014) 1005-LBP Human Immunology. 75: 480 |
| Cai F, Cherkassky V. (2012) Generalized SMO algorithm for SVM-based multitask learning. Ieee Transactions On Neural Networks and Learning Systems. 23: 997-1003 |
| Cherkassky V. (2012) The nature of statistical learning theory~. Ieee Transactions On Neural Networks. 8: 1564 |
| Shiao HT, Cherkassky V. (2012) Implementation and comparison of SVM-based Multi-Task Learning methods Proceedings of the International Joint Conference On Neural Networks |
| Dhar S, Cherkassky V. (2012) Cost-sensitive universum-SVM Proceedings - 2012 11th International Conference On Machine Learning and Applications, Icmla 2012. 1: 220-225 |