公開日期 | 標題 | 作者 | 來源出版物 | scopus | WOS | 全文 |
2021 | On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition | Bai C.-Y; Raffel C; Kan W.C.-W.; HSUAN-TIEN LIN | Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining | 5 | 0 | |
2010 | One-sided Support Vector Regression for Multiclass Cost-sensitive Classification | Tu, Han-Hsing; Lin, Hsuan-Tien | 27th International Conference on Machine Learning | | | |
2012 | An Online Boosting Algorithm with Theoretical Justifications | Chen, Shang-Tse; Lin, Hsuan-Tien ; Lu, Chi-Jen | 29th International Conference on Machine Learning | | | |
2007 | Optimizing 0/1 loss for perceptrons by random coordinate descent | Li, L.; HSUAN-TIEN LIN | IEEE International Conference on Neural Networks | 9 | 0 | |
2007 | Ordinal regression by extended binary classification | Li, L.; HSUAN-TIEN LIN | Advances in Neural Information Processing Systems | | | |
2013 | Pairwise regression with upper confidence bound for contextual bandit with multiple actions | Chang, Y.-H.; HSUAN-TIEN LIN | 2013 Conference on Technologies and Applications of Artificial Intelligence | 0 | 0 | |
2016 | A practical divide-and-conquer approach for preference-based learning to rank | Yang, H.-J.; HSUAN-TIEN LIN | TAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence | 1 | 0 | |
2017 | Progressive random k-labelsets for cost-sensitive multi-label classification | Wu, Y.-P.; HSUAN-TIEN LIN | Machine Learning | | | |
2012 | Reduction from cost-sensitive ordinal ranking to weighted binary classification | Li, Ling; Lin, Hsuan-Tien | Neural Computation | 91 | 76 | |
2023 | Reduction from Complementary-Label Learning to Probability Estimates | Lin, Wei I.; HSUAN-TIEN LIN | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | 1 | 0 | |
2018 | Refuel: Exploring sparse features in deep reinforcement learning for fast disease diagnosis | Peng Y.-S; Tang K.-F; Chang E.Y; HSUAN-TIEN LIN | Advances in Neural Information Processing Systems | | | |
2018 | Rotation-blended CNNs on a new open dataset for tropical cyclone image-to-intensity regression | Chen, B.; Chen, B.-F.; HSUAN-TIEN LIN | Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining | 44 | 0 | |
2020 | SERIL: Noise adaptive speech enhancement using regularization-based incremental learning | Lee C.-C; Lin Y.-C; Wang H.-M; Tsao Y.; HSUAN-TIEN LIN | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH | 5 | 0 | |
2016 | A Simple Unlearning Framework for Online Learning Under Concept Drifts. | You, Sheng-Chi; HSUAN-TIEN LIN | Advances in Knowledge Discovery and Data Mining - 20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part I | | | |
2005 | a study on sigmoid kernels for svm and the training of non-psd | Lin, Hsuan-Tien ; Lin, Chih-Jen | | | | |
2008 | Support Vector Machinery for Infinite Ensemble Learning | Lin, Hsuan-Tien ; Li, Ling | Journal of Machine Learning Research | | | |
2012 | Teaching Machine Learning to a Diverse Audience: the Foundation-based Approach | Lin, Hsuan-Tien ; Magdon-Ismail, Malik; Abu-Mostafa, Yaser S. | ICML | | | |
2012 | A Two-Stage Ensemble of Diverse Models for Advertisement Ranking in KDD Cup 2012 | Wu, Kuan-Wei; Lin, Shou-De ; Lin, Hsuan-Tien et al. | KDDCup | | | |
2020 | Unbiased risk estimators can mislead: A case study of learning with complementary labels | Chou Y.-T; Niu G; Lin H.-T; Sugiyama M.; HSUAN-TIEN LIN | 37th International Conference on Machine Learning, ICML 2020 | | | |
2021 | A Unified View of cGANs with and without Classifiers | Chen S.-A; Li C.-L; HSUAN-TIEN LIN | Advances in Neural Information Processing Systems | 2 | | |