Hsuan-Tien Lin

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 79

Top Venues

Publications

Xiwei Xuan, Ziquan Deng, Hsuan-Tien Lin, Kwan-Liu Ma
SLIM: Spuriousness Mitigation with Minimal Human Annotations. CoRR (2024)
Oscar Chew, Hsuan-Tien Lin, Kai-Wei Chang, Kuan-Hao Huang
Understanding and Mitigating Spurious Correlations in Text Classification with Neighborhood Analysis. EACL (Findings) (2024)
Vo Nguyen Le Duy, Hsuan-Tien Lin, Ichiro Takeuchi
CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference. AISTATS (2024)
Wei-Chao Cheng, Tan-Ha Mai, Hsuan-Tien Lin
From SMOTE to Mixup for Deep Imbalanced Classification. CoRR (2023)
Chien-Min Yu, Ming-Hsin Chen, Hsuan-Tien Lin
Learning key steps to attack deep reinforcement learning agents. Mach. Learn. 112 (5) (2023)
Hsiu-Hsuan Wang, Wei-I Lin, Hsuan-Tien Lin
CLCIFAR: CIFAR-Derived Benchmark Datasets with Human Annotated Complementary Labels. CoRR (2023)
Wei-Chao Cheng, Tan-Ha Mai, Hsuan-Tien Lin
From SMOTE to Mixup for Deep Imbalanced Classification. TAAI (1) (2023)
Yu-Chu Yu, Hsuan-Tien Lin
Semi-Supervised Domain Adaptation with Source Label Adaptation. CVPR (2023)
Wei-I Lin, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama
Enhancing Label Sharing Efficiency in Complementary-Label Learning with Label Augmentation. CoRR (2023)
Vo Nguyen Le Duy, Hsuan-Tien Lin, Ichiro Takeuchi
CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference. CoRR (2023)
Yu-Chu Yu, Hsuan-Tien Lin
Semi-Supervised Domain Adaptation with Source Label Adaptation. CoRR (2023)
Xiwei Xuan, Ziquan Deng, Hsuan-Tien Lin, Zhaodan Kong, Kwan-Liu Ma
SUNY: A Visual Interpretation Framework for Convolutional Neural Networks from a Necessary and Sufficient Perspective. CoRR (2023)
Oscar Chew, Kuan-Hao Huang, Kai-Wei Chang, Hsuan-Tien Lin
Understanding and Mitigating Spurious Correlations in Text Classification. CoRR (2023)
Po-Yi Lu, Chun-Liang Li, Hsuan-Tien Lin
Re-Benchmarking Pool-Based Active Learning for Binary Classification. CoRR (2023)
Wei-I Lin, Hsuan-Tien Lin
Reduction from Complementary-Label Learning to Probability Estimates. PAKDD (2) (2023)
Paul Kuo-Ming Huang, Si-An Chen, Hsuan-Tien Lin
Score-based Conditional Generation with Fewer Labeled Data by Self-calibrating Classifier Guidance. CoRR (2023)
Wei-I Lin, Hsuan-Tien Lin
Reduction from Complementary-Label Learning to Probability Estimates. CoRR (2022)
Si-An Chen, Jie-Jyun Liu, Tsung-Han Yang, Hsuan-Tien Lin, Chih-Jen Lin
Even the Simplest Baseline Needs Careful Re-investigation: A Case Study on XML-CNN. NAACL-HLT (2022)
Sheng-Feng Wu, Hsuan-Tien Lin
Improving Clustering Uncertainty-weighted Embeddings for Active Domain Adaptation. TAAI (2022)
Andrew Bai, Cho-Jui Hsieh, Wendy Chi-wen Kan, Hsuan-Tien Lin
Reducing Training Sample Memorization in GANs by Training with Memorization Rejection. CoRR (2022)
Ashesh, Buo-Fu Chen, Treng-Shi Huang, Boyo Chen, Chia-Tung Chang, Hsuan-Tien Lin
Accurate and Clear Precipitation Nowcasting with Consecutive Attention and Rain-map Discrimination. CoRR (2021)
Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin
A Unified View of cGANs with and without Classifiers. CoRR (2021)
Ching-Yuan Bai, Hsuan-Tien Lin, Colin Raffel, Wendy Chih-wen Kan
On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition. CoRR (2021)
Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin
A Unified View of cGANs with and without Classifiers. NeurIPS (2021)
Yu-Ying Chou, Hsuan-Tien Lin, Tyng-Luh Liu
Adaptive and Generative Zero-Shot Learning. ICLR (2021)
Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin
Improving Model Compatibility of Generative Adversarial Networks by Boundary Calibration. CoRR (2021)
Ashesh, Chu-Song Chen, Hsuan-Tien Lin
360-Degree Gaze Estimation in the Wild Using Multiple Zoom Scales. BMVC (2021)
Ching-Yuan Bai, Hsuan-Tien Lin, Colin Raffel, Wendy Chi-wen Kan
On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition. KDD (2021)
Cheng-Yu Hsieh, Wei-I Lin, Miao Xu, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama
Active Refinement for Multi-Label Learning: A Pseudo-Label Approach. CoRR (2021)
Kuen-Han Tsai, Hsuan-Tien Lin
Learning from Label Proportions with Consistency Regularization. ACML (2020)
Ching-Yuan Bai, Buo-Fu Chen, Hsuan-Tien Lin
Benchmarking Tropical Cyclone Rapid Intensification with Satellite Images and Attention-Based Deep Models. ECML/PKDD (4) (2020)
Yu-An Chung, Shao-Wen Yang, Hsuan-Tien Lin
Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation. TAAI (2020)
Michelle Yuan, Hsuan-Tien Lin, Jordan L. Boyd-Graber
Cold-start Active Learning through Self-supervised Language Modeling. CoRR (2020)
Michelle Yuan, Hsuan-Tien Lin, Jordan L. Boyd-Graber
Cold-start Active Learning through Self-supervised Language Modeling. EMNLP (1) (2020)
I-Ting Chen, Hsuan-Tien Lin
Improving Unsupervised Domain Adaptation with Representative Selection Techniques. IAL@PKDD/ECML (2020)
Ashesh Mishra, Hsuan-Tien Lin
360-Degree Gaze Estimation in the Wild Using Multiple Zoom Scales. CoRR (2020)
Chi-Chang Lee, Yu-Chen Lin, Hsuan-Tien Lin, Hsin-Min Wang, Yu Tsao
SERIL: Noise Adaptive Speech Enhancement using Regularization-based Incremental Learning. CoRR (2020)
Yu-Ting Chou, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama
Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels. ICML (2020)
Si-An Chen, Voot Tangkaratt, Hsuan-Tien Lin, Masashi Sugiyama
Active deep Q-learning with demonstration. Mach. Learn. 109 (9-10) (2020)
Chun-Yi Tu, Hsuan-Tien Lin
Cost Learning Network for Imbalanced Classification. TAAI (2020)
Yu-Ting Chou, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama
Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels. CoRR (2020)
Chi-Chang Lee, Yu-Chen Lin, Hsuan-Tien Lin, Hsin-Min Wang, Yu Tsao
SERIL: Noise Adaptive Speech Enhancement Using Regularization-Based Incremental Learning. INTERSPEECH (2020)
Kuen-Han Tsai, Hsuan-Tien Lin
Learning from Label Proportions with Consistency Regularization. CoRR (2019)
Yao-Yuan Yang, Yi-An Lin, Hong-Min Chu, Hsuan-Tien Lin
Deep Learning with a Rethinking Structure for Multi-label Classification. ACML (2019)
Ching-Yuan Bai, Buo-Fu Chen, Hsuan-Tien Lin
Attention-based Deep Tropical Cyclone Rapid Intensification Prediction. MACLEAN@PKDD/ECML (2019)
Hong-Min Chu, Kuan-Hao Huang, Hsuan-Tien Lin
Dynamic principal projection for cost-sensitive online multi-label classification. Mach. Learn. 108 (8-9) (2019)
Yu-Lin Tsou, Hsuan-Tien Lin
Annotation cost-sensitive active learning by tree sampling. Mach. Learn. 108 (5) (2019)
Ching-Yuan Bai, Buo-Fu Chen, Hsuan-Tien Lin
Attention-based Deep Tropical Cyclone Rapid Intensification Prediction. CoRR (2019)
Hsuan-Tien Lin
Advances in Cost-sensitive Multiclass and Multilabel Classification. KDD (2019)
Yao-Yuan Yang, Kuan-Hao Huang, Chih-Wei Chang, Hsuan-Tien Lin
Cost-Sensitive Reference Pair Encoding for Multi-Label Learning. PAKDD (1) (2018)
Yu-Shao Peng, Kai-Fu Tang, Hsuan-Tien Lin, Edward Y. Chang
REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis. NeurIPS (2018)
Yao-Yuan Yang, Yi-An Lin, Hong-Min Chu, Hsuan-Tien Lin
Deep Learning with a Rethinking Structure for Multi-label Classification. CoRR (2018)
Cheng-Yu Hsieh, Yi-An Lin, Hsuan-Tien Lin
A Deep Model With Local Surrogate Loss for General Cost-Sensitive Multi-Label Learning. AAAI (2018)
Si-An Chen, Voot Tangkaratt, Hsuan-Tien Lin, Masashi Sugiyama
Active Deep Q-learning with Demonstration. CoRR (2018)
Boyo Chen, Buo-Fu Chen, Hsuan-Tien Lin
Rotation-blended CNNs on a New Open Dataset for Tropical Cyclone Image-to-intensity Regression. KDD (2018)
Chih-Kuan Yeh, Cheng-Yu Hsieh, Hsuan-Tien Lin
Automatic Bridge Bidding Using Deep Reinforcement Learning. IEEE Trans. Games 10 (4) (2018)
Hsien-Chun Chiu, Hsuan-Tien Lin
Multi-Label Classification with Feature-Aware Cost-Sensitive Label Embedding. TAAI (2018)
Yong-Siang Shih, Kai-Yueh Chang, Hsuan-Tien Lin, Min Sun
Compatibility Family Learning for Item Recommendation and Generation. AAAI (2018)
Yuping Wu, Hsuan-Tien Lin
Progressive random k-labelsets for cost-sensitive multi-label classification. Mach. Learn. 106 (5) (2017)
Yong-Siang Shih, Kai-Yueh Chang, Hsuan-Tien Lin, Min Sun
Compatibility Family Learning for Item Recommendation and Generation. CoRR (2017)
Kuo-Hsuan Lo, Hsuan-Tien Lin
Cost-Sensitive Encoding for Label Space Dimension Reduction Algorithms on Multi-label Classification. TAAI (2017)
Kuan-Hao Huang, Hsuan-Tien Lin
Cost-sensitive label embedding for multi-label classification. Mach. Learn. 106 (9-10) (2017)
Te-Kang Jan, Da-Wei Wang, Chi-Hung Lin, Hsuan-Tien Lin
Soft Methodology for Cost-and-error Sensitive Classification. CoRR (2017)
Wei-Yuan Shen, Hsuan-Tien Lin
Active Sampling of Pairs and Points for Large-scale Linear Bipartite Ranking. CoRR (2017)
Hong-Min Chu, Kuan-Hao Huang, Hsuan-Tien Lin
Dynamic Principal Projection for Cost-Sensitive Online Multi-Label Classification. CoRR (2017)
Yi-An Lin, Hsuan-Tien Lin
Cyclic Classifier Chain for Cost-Sensitive Multilabel Classification. DSAA (2017)
Yao-Yuan Yang, Shao-Chuan Lee, Yu-An Chung, Tung-En Wu, Si-An Chen, Hsuan-Tien Lin
libact: Pool-based Active Learning in Python. CoRR (2017)
Kuan-Hao Huang, Hsuan-Tien Lin
A Novel Uncertainty Sampling Algorithm for Cost-Sensitive Multiclass Active Learning. ICDM (2016)
Yao-Yuan Yang, Chih-Wei Chang, Hsuan-Tien Lin
Cost-Sensitive Random Pair Encoding for Multi-Label Classification. CoRR (2016)
Hong-Min Chu, Hsuan-Tien Lin
Can Active Learning Experience Be Transferred? ICDM (2016)
Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu
Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA. AISTATS (2016)
Yu-An Chung, Hsuan-Tien Lin, Shao-Wen Yang
Cost-Aware Pre-Training for Multiclass Cost-Sensitive Deep Learning. IJCAI (2016)
Chih-Kuan Yeh, Hsuan-Tien Lin
Automatic Bridge Bidding Using Deep Reinforcement Learning. CoRR (2016)
Kuan-Hao Huang, Hsuan-Tien Lin
Cost-sensitive Label Embedding for Multi-label Classification. CoRR (2016)
Sheng-Chi You, Hsuan-Tien Lin
A Simple Unlearning Framework for Online Learning Under Concept Drifts. PAKDD (1) (2016)
Chih-Kuan Yeh, Hsuan-Tien Lin
Automatic Bridge Bidding Using Deep Reinforcement Learning. ECAI (2016)
Hong-Min Chu, Hsuan-Tien Lin
Can Active Learning Experience Be Transferred? CoRR (2016)
Kuan-Hao Huang, Hsuan-Tien Lin
Linear Upper Confidence Bound Algorithm for Contextual Bandit Problem with Piled Rewards. PAKDD (2) (2016)
Yu-An Chung, Hsuan-Tien Lin
Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation. CoRR (2016)
Wei-Ning Hsu, Hsuan-Tien Lin
Active Learning by Learning. AAAI (2015)
Yu-An Chung, Hsuan-Tien Lin, Shao-Wen Yang
Cost-aware Pre-training for Multiclass Cost-sensitive Deep Learning. CoRR (2015)
Chun-Yen Ho, Hsuan-Tien Lin
Contract Bridge Bidding by Learning. AAAI Workshop: Computer Poker and Imperfect Information (2015)
Han-Jay Yang, Hsuan-Tien Lin
A practical divide-and-conquer approach for preference-based learning to rank. TAAI (2015)
Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu
Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA. CoRR (2015)
Chun-Liang Li, Chun-Sung Ferng, Hsuan-Tien Lin
Active Learning Using Hint Information. Neural Comput. 27 (8) (2015)
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
Combination of feature engineering and ranking models for paper-author identification in KDD cup 2013. J. Mach. Learn. Res. 16 (2015)
Yu-Cheng Chou, Hsuan-Tien Lin
Machine Learning Approaches for Interactive Verification. PAKDD (2) (2014)
Hsuan-Tien Lin
Reduction from Cost-Sensitive Multiclass Classification to One-versus-One Binary Classification. ACML (2014)
Yu-Xun Ruan, Hsuan-Tien Lin, Ming-Feng Tsai
Improving ranking performance with cost-sensitive ordinal classification via regression. Inf. Retr. 17 (1) (2014)
Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu
Boosting with Online Binary Learners for the Multiclass Bandit Problem. ICML (2014)
Chun-Liang Li, Hsuan-Tien Lin
Condensed Filter Tree for Cost-Sensitive Multi-Label Classification. ICML (2014)
Wei-Sheng Chin, Yong Zhuang, Yu-Chin Juan, 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
Effective string processing and matching for author disambiguation. J. Mach. Learn. Res. 15 (1) (2014)
Ku-Chun Chou, Hsuan-Tien Lin, Chao-Kai Chiang, Chi-Jen Lu
Pseudo-reward Algorithms for Contextual Bandits with Linear Payoff Functions. ACML (2014)
Wei-Yuan Shen, Hsuan-Tien Lin
Active Sampling of Pairs and Points for Large-scale Linear Bipartite Ranking. ACML (2013)
Chun-Sung Ferng, Hsuan-Tien Lin
Multilabel Classification Using Error-Correcting Codes of Hard or Soft Bits. IEEE Trans. Neural Networks Learn. Syst. 24 (11) (2013)
Ya-Hsuan Chang, Hsuan-Tien Lin
Pairwise Regression with Upper Confidence Bound for Contextual Bandit with Multiple Actions. TAAI (2013)
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
Effective string processing and matching for author disambiguation. 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
Combination of feature engineering and ranking models for paper-author identification in KDD Cup 2013. KDD Cup (2013)
Po-Lung Chen, Hsuan-Tien Lin
Active Learning for Multiclass Cost-Sensitive Classification Using Probabilistic Models. TAAI (2013)
Ken-Yi Lin, Te-Kang Jan, Hsuan-Tien Lin
Data Selection Techniques for Large-Scale Rank SVM. TAAI (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Hsuan-Tien Lin