| Incremental support vector learning for ordinal regression B Gu, VS Sheng, KY Tay, W Romano, S Li IEEE Transactions on Neural networks and learning systems 26 (7), 1403-1416, 2014 | 722 | 2014 |
| A Robust Regularization Path Algorithm for -Support Vector Classification B Gu, VS Sheng IEEE Transactions on neural networks and learning systems 28 (5), 1241-1248, 2016 | 505 | 2016 |
| Incremental learning for í-support vector regression B Gu, VS Sheng, Z Wang, D Ho, S Osman, S Li Neural networks 67, 140-150, 2015 | 458 | 2015 |
| Structural minimax probability machine B Gu, X Sun, VS Sheng IEEE Transactions on Neural Networks and Learning Systems 28 (7), 1646-1656, 2016 | 352 | 2016 |
| Bi-parameter space partition for cost-sensitive SVM B Gu, VS Sheng, S Li Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015 | 68 | 2015 |
| Direct estimation of cardiac biventricular volumes with an adapted bayesian formulation Z Wang, MB Salah, B Gu, A Islam, A Goela, S Li IEEE Transactions on Biomedical Engineering 61 (4), 1251-1260, 2014 | 68 | 2014 |
| Cross validation through two-dimensional solution surface for cost-sensitive SVM B Gu, VS Sheng, KY Tay, W Romano, S Li IEEE transactions on pattern analysis and machine intelligence 39 (6), 1103-1121, 2016 | 56 | 2016 |
| Decoupled parallel backpropagation with convergence guarantee Z Huo, B Gu, H Huang International Conference on Machine Learning, 2098-2106, 2018 | 55 | 2018 |
| Feasibility and Finite Convergence Analysis for Accurate On-Line -Support Vector Machine B Gu, VS Sheng IEEE Transactions on Neural Networks and Learning Systems 24 (8), 1304-1315, 2013 | 54 | 2013 |
| Training neural networks using features replay Z Huo, B Gu, H Huang Advances in Neural Information Processing Systems 31, 2018 | 52 | 2018 |
| Chunk incremental learning for cost-sensitive hinge loss support vector machine B Gu, X Quan, Y Gu, VS Sheng, G Zheng Pattern Recognition 83, 196-208, 2018 | 45 | 2018 |
| Privacy-preserving asynchronous vertical federated learning algorithms for multiparty collaborative learning B Gu, A Xu, Z Huo, C Deng, H Huang IEEE transactions on neural networks and learning systems, 2021 | 43* | 2021 |
| Majority voting and pairing with multiple noisy labeling VS Sheng, J Zhang, B Gu, X Wu IEEE Transactions on Knowledge and Data Engineering 31 (7), 1355-1368, 2017 | 37 | 2017 |
| Accelerated method for stochastic composition optimization with nonsmooth regularization Z Huo, B Gu, J Liu, H Huang Thirty-Second AAAI Conference on Artificial Intelligence, 2018 | 36 | 2018 |
| Inexact Proximal Gradient Methods for Non-Convex and Non-Smooth Optimization B Gu, D Wang, Z Huo, H Huang The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), 3093 …, 2018 | 34 | 2018 |
| Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines B Gu, Z Huo, C Deng, H Huang International Conference on Machine Learning, 2018 | 33* | 2018 |
| Cost-sensitive learning for defect escalation VS Sheng, B Gu, W Fang, J Wu Knowledge-Based Systems 66, 146-155, 2014 | 33 | 2014 |
| Federated doubly stochastic kernel learning for vertically partitioned data B Gu, Z Dang, X Li, H Huang Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 29 | 2020 |
| Faster on-device training using new federated momentum algorithm Z Huo, Q Yang, B Gu, LC Huang arXiv preprint arXiv:2002.02090, 2020 | 29 | 2020 |
| Accurate on-line í-support vector learning B Gu, JD Wang, YC Yu, GS Zheng, YF Huang, T Xu Neural Networks 27, 51-59, 2012 | 26 | 2012 |
Heng HuangJohn A. Jurenko Endowed Professor, Electrical and Computer Engineering, University of PittsburghVerified email at pitt.edu
