| 2025 | ICCV | Soft Separation and Distillation: Toward Global Uniformity in Federated Unsupervised Learning. | Hung-Chieh Fang, Hsuan-Tien Lin, Irwin King, Yifei Zhang |
| 2025 | ICML | Tackling Dimensional Collapse toward Comprehensive Universal Domain Adaptation. | Hung-Chieh Fang, Po-Yi Lu, Hsuan-Tien Lin |
| 2025 | NAACL | Preserving Zero-shot Capability in Supervised Fine-tuning for Multi-label Text Classification. | Si-An Chen, Hsuan-Tien Lin, Chih-Jen Lin |
| 2025 | PAKDD | The Unexplored Potential of Vision-Language Models for Generating Large-Scale Complementary-Label Learning Data. | Tan-Ha Mai, Nai-Xuan Ye, Yu-Wei Kuan, Po-Yi Lu, Hsuan-Tien Lin |
| 2024 | AISTATS | CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference. | Vo Nguyen Le Duy, Hsuan-Tien Lin, Ichiro Takeuchi |
| 2024 | EACL | Understanding and Mitigating Spurious Correlations in Text Classification with Neighborhood Analysis. | Oscar Chew, Hsuan-Tien Lin, Kai-Wei Chang, Kuan-Hao Huang |
| 2024 | ECCV | SLIM: Spuriousness Mitigation with Minimal Human Annotations. | Xiwei Xuan, Ziquan Deng, Hsuan-Tien Lin, Kwan-Liu Ma |
| 2023 | CVPR | Semi-Supervised Domain Adaptation with Source Label Adaptation. | Yu-Chu Yu, Hsuan-Tien Lin |
| 2023 | PAKDD | Reduction from Complementary-Label Learning to Probability Estimates. | Wei-I Lin, Hsuan-Tien Lin |
| 2022 | NAACL | Even the Simplest Baseline Needs Careful Re-investigation: A Case Study on XML-CNN. | Si-An Chen, Jie-Jyun Liu, Tsung-Han Yang, Hsuan-Tien Lin, Chih-Jen Lin |
| 2021 | BMVC | 360-Degree Gaze Estimation in the Wild Using Multiple Zoom Scales. | Ashesh, Chu-Song Chen, Hsuan-Tien Lin |
| 2021 | ICLR | Adaptive and Generative Zero-Shot Learning. | Yu-Ying Chou, Hsuan-Tien Lin, Tyng-Luh Liu |
| 2021 | KDD | On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition. | Ching-Yuan Bai, Hsuan-Tien Lin, Colin Raffel, Wendy Chi-wen Kan |
| 2020 | ACML | Learning from Label Proportions with Consistency Regularization. | Kuen-Han Tsai, Hsuan-Tien Lin |
| 2020 | EMNLP | Cold-start Active Learning through Self-supervised Language Modeling. | Michelle Yuan, Hsuan-Tien Lin, Jordan L. Boyd-Graber |
| 2020 | ICML | Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels. | Yu-Ting Chou, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama |
| 2020 | Interspeech | SERIL: Noise Adaptive Speech Enhancement Using Regularization-Based Incremental Learning. | Chi-Chang Lee, Yu-Chen Lin, Hsuan-Tien Lin, Hsin-Min Wang, Yu Tsao |
| 2019 | ACML | Deep Learning with a Rethinking Structure for Multi-label Classification. | Yao-Yuan Yang, Yi-An Lin, Hong-Min Chu, Hsuan-Tien Lin |
| 2019 | KDD | Advances in Cost-sensitive Multiclass and Multilabel Classification. | Hsuan-Tien Lin |
| 2018 | AAAI | A Deep Model With Local Surrogate Loss for General Cost-Sensitive Multi-Label Learning. | Cheng-Yu Hsieh, Yi-An Lin, Hsuan-Tien Lin |
| 2018 | AAAI | Compatibility Family Learning for Item Recommendation and Generation. | Yong-Siang Shih, Kai-Yueh Chang, Hsuan-Tien Lin, Min Sun |
| 2018 | KDD | Rotation-blended CNNs on a New Open Dataset for Tropical Cyclone Image-to-intensity Regression. | Boyo Chen, Buo-Fu Chen, Hsuan-Tien Lin |
| 2018 | PAKDD | Cost-Sensitive Reference Pair Encoding for Multi-Label Learning. | Yao-Yuan Yang, Kuan-Hao Huang, Chih-Wei Chang, Hsuan-Tien Lin |
| 2017 | DSAA | Cyclic Classifier Chain for Cost-Sensitive Multilabel Classification. | Yi-An Lin, Hsuan-Tien Lin |
| 2016 | AISTATS | Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA. | Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu |
| 2016 | ECAI | Automatic Bridge Bidding Using Deep Reinforcement Learning. | Chih-Kuan Yeh, Hsuan-Tien Lin |
| 2016 | ICDM | Can Active Learning Experience Be Transferred? | Hong-Min Chu, Hsuan-Tien Lin |
| 2016 | ICDM | A Novel Uncertainty Sampling Algorithm for Cost-Sensitive Multiclass Active Learning. | Kuan-Hao Huang, Hsuan-Tien Lin |
| 2016 | IJCAI | Cost-Aware Pre-Training for Multiclass Cost-Sensitive Deep Learning. | Yu-An Chung, Hsuan-Tien Lin, Shao-Wen Yang |
| 2016 | PAKDD | Linear Upper Confidence Bound Algorithm for Contextual Bandit Problem with Piled Rewards. | Kuan-Hao Huang, Hsuan-Tien Lin |
| 2016 | PAKDD | A Simple Unlearning Framework for Online Learning Under Concept Drifts. | Sheng-Chi You, Hsuan-Tien Lin |
| 2015 | AAAI | Contract Bridge Bidding by Learning. | Chun-Yen Ho, Hsuan-Tien Lin |
| 2015 | AAAI | Active Learning by Learning. | Wei-Ning Hsu, Hsuan-Tien Lin |
| 2014 | ACML | Pseudo-reward Algorithms for Contextual Bandits with Linear Payoff Functions. | Ku-Chun Chou, Hsuan-Tien Lin, Chao-Kai Chiang, Chi-Jen Lu |
| 2014 | ACML | Reduction from Cost-Sensitive Multiclass Classification to One-versus-One Binary Classification. | Hsuan-Tien Lin |
| 2014 | ICML | Boosting with Online Binary Learners for the Multiclass Bandit Problem. | Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu |
| 2014 | ICML | Condensed Filter Tree for Cost-Sensitive Multi-Label Classification. | Chun-Liang Li, Hsuan-Tien Lin |
| 2014 | PAKDD | Machine Learning Approaches for Interactive Verification. | Yu-Cheng Chou, Hsuan-Tien Lin |
| 2013 | ACML | Active Sampling of Pairs and Points for Large-scale Linear Bipartite Ranking. | Wei-Yuan Shen, Hsuan-Tien Lin |
| 2013 | KDD | Effective string processing and matching for author disambiguation. | Wei-Sheng Chin, Yu-Chin Juan, Yong Zhuang, Felix Wu, Hsiao-Yu Tung, Tong Yu, Jui-Pin Wang, Cheng-Xia Chang, Chun-Pai Yang, Wei-Cheng Chang, Kuan-Hao Huang, Tzu-Ming Kuo, Shan-Wei Lin, Young-San Lin, Yu-Chen Lu, Yu-Chuan Su, Cheng-Kuang Wei, Tu-Chun Yin, Chun-Liang Li, Ting-Wei Lin, Cheng-Hao Tsai, Shou-De Lin, Hsuan-Tien Lin, Chih-Jen Lin |
| 2013 | KDD | Combination of feature engineering and ranking models for paper-author identification in KDD Cup 2013. | Chun-Liang Li, Yu-Chuan Su, Ting-Wei Lin, Cheng-Hao Tsai, Wei-Cheng Chang, Kuan-Hao Huang, Tzu-Ming Kuo, Shan-Wei Lin, Young-San Lin, Yu-Chen Lu, Chun-Pai Yang, Cheng-Xia Chang, Wei-Sheng Chin, Yu-Chin Juan, Hsiao-Yu Tung, Jui-Pin Wang, Cheng-Kuang Wei, Felix Wu, Tu-Chun Yin, Tong Yu, Yong Zhuang, Shou-de Lin, Hsuan-Tien Lin, Chih-Jen Lin |
| 2012 | ICML | An Online Boosting Algorithm with Theoretical Justifications. | Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu |
| 2012 | KDD | A simple methodology for soft cost-sensitive classification. | Te-Kang Jan, Da-Wei Wang, Chi-Hung Lin, Hsuan-Tien Lin |
| 2011 | CVPR | Unsupervised auxiliary visual words discovery for large-scale image object retrieval. | Yin-Hsi Kuo, Hsuan-Tien Lin, Wen-Huang Cheng, Yi-Hsuan Yang, Winston H. Hsu |
| 2010 | ICML | One-sided Support Vector Regression for Multiclass Cost-sensitive Classification. | Han-Hsing Tu, Hsuan-Tien Lin |
| 2007 | IJCNN | Optimizing 0/1 Loss for Perceptrons by Random Coordinate Descent. | Ling Li, Hsuan-Tien Lin |
| 2006 | ALT | Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice. | Hsuan-Tien Lin, Ling Li |