Hsuan-Tien Lin

144 papers A* 23A 5B 3C 9Journal 67Unranked 36

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Expanding the Role of Diffusion Models for Robust Classifier Training. CoRR Pin-Han Huang, Shang-Tse Chen, Hsuan-Tien Lin
2026	J	`jnl`	Intra-Cluster Mixup: An Effective Data Augmentation Technique for Complementary-Label Learning. Trans. Mach. Learn. Res. Tan-Ha Mai, Hsuan-Tien Lin
2025	J	`jnl`	An Expanded Benchmark that Rediscovers and Affirms the Edge of Uncertainty Sampling for Active Learning in Tabular Datasets. Trans. Mach. Learn. Res. Po-Yi Lu, Yi-Jie Cheng, Chun-Liang Li, Hsuan-Tien Lin
2025	J	`jnl`	CLImage: Human-Annotated Datasets for Complementary-Label Learning. Trans. Mach. Learn. Res. Hsiu-Hsuan Wang, Tan-Ha Mai, Nai-Xuan Ye, Wei-I Lin, Hsuan-Tien Lin
2025	J	`jnl`	Intra-Cluster Mixup: An Effective Data Augmentation Technique for Complementary-Label Learning. CoRR Tan-Ha Mai, Hsuan-Tien Lin
2025	J	`jnl`	PEPPER: Perception-Guided Perturbation for Robust Backdoor Defense in Text-to-Image Diffusion Models. CoRR Oscar Chew, Po-Yi Lu, Jayden Lin, Kuan-Hao Huang, Hsuan-Tien Lin
2025	—	`conf`	Preserving Zero-shot Capability in Supervised Fine-tuning for Multi-label Text Classification. NAACL (Findings) Si-An Chen, Hsuan-Tien Lin, Chih-Jen Lin
2025	J	`jnl`	Soft Separation and Distillation: Toward Global Uniformity in Federated Unsupervised Learning. CoRR Hung-Chieh Fang, Hsuan-Tien Lin, Irwin King, Yifei Zhang
2025	A*	`conf`	Tackling Dimensional Collapse toward Comprehensive Universal Domain Adaptation. ICML Hung-Chieh Fang, Po-Yi Lu, Hsuan-Tien Lin
2025	—	`conf`	The Unexplored Potential of Vision-Language Models for Generating Large-Scale Complementary-Label Learning Data. PAKDD (5) Tan-Ha Mai, Nai-Xuan Ye, Yu-Wei Kuan, Po-Yi Lu, Hsuan-Tien Lin
2024	C	`ed.`	Asian Conference on Machine Learning, 5-8 December 2024, Hanoi, Vietnam. ACML Vu Nguyen, Hsuan-Tien Lin
2024	A	`conf`	CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference. AISTATS Vo Nguyen Le Duy, Hsuan-Tien Lin, Ichiro Takeuchi
2024	J	`jnl`	Defending Text-to-image Diffusion Models: Surprising Efficacy of Textual Perturbations Against Backdoor Attacks. CoRR Oscar Chew, Po-Yi Lu, Jayden Lin, Hsuan-Tien Lin
2024	J	`jnl`	MAX: Masked Autoencoder for X-ray Fluorescence in Geological Investigation. CoRR An-Sheng Lee, Yu-Wen Pao, Hsuan-Tien Lin, Sofia Ya Hsuan Liou
2024	J	`jnl`	Reducing Source-Private Bias in Extreme Universal Domain Adaptation. CoRR Hung-Chieh Fang, Po-Yi Lu, Hsuan-Tien Lin
2024	—	`conf`	SLIM: Spuriousness Mitigation with Minimal Human Annotations. ECCV (46) Xiwei Xuan, Ziquan Deng, Hsuan-Tien Lin, Kwan-Liu Ma
2024	J	`jnl`	SLIM: Spuriousness Mitigation with Minimal Human Annotations. CoRR Xiwei Xuan, Ziquan Deng, Hsuan-Tien Lin, Kwan-Liu Ma
2024	—	`conf`	SUNY: A Visual Interpretation Framework for Convolutional Neural Networks from a Necessary and Sufficient Perspective. XAI4CV Xiwei Xuan, Ziquan Deng, Hsuan-Tien Lin, Zhaodan Kong, Kwan-Liu Ma
2024	A*	`conf`	TableRAG: Million-Token Table Understanding with Language Models. NeurIPS Si-An Chen, Lesly Miculicich, Julian Eisenschlos, Zifeng Wang, Zilong Wang, Yanfei Chen, Yasuhisa Fujii, Hsuan-Tien Lin, Chen-Yu Lee, Tomas Pfister
2024	J	`jnl`	TableRAG: Million-Token Table Understanding with Language Models. CoRR Si-An Chen, Lesly Miculicich, Julian Martin Eisenschlos, Zifeng Wang, Zilong Wang, Yanfei Chen, Yasuhisa Fujii, Hsuan-Tien Lin, Chen-Yu Lee, Tomas Pfister
2024	—	`conf`	Understanding and Mitigating Spurious Correlations in Text Classification with Neighborhood Analysis. EACL (Findings) Oscar Chew, Hsuan-Tien Lin, Kai-Wei Chang, Kuan-Hao Huang
2024	J	`jnl`	libcll: an Extendable Python Toolkit for Complementary-Label Learning. CoRR Nai-Xuan Ye, Tan-Ha Mai, Hsiu-Hsuan Wang, Wei-I Lin, Hsuan-Tien Lin
2023	J	`jnl`	CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference. CoRR Vo Nguyen Le Duy, Hsuan-Tien Lin, Ichiro Takeuchi
2023	J	`jnl`	CLCIFAR: CIFAR-Derived Benchmark Datasets with Human Annotated Complementary Labels. CoRR Hsiu-Hsuan Wang, Wei-I Lin, Hsuan-Tien Lin
2023	J	`jnl`	Enhancing Label Sharing Efficiency in Complementary-Label Learning with Label Augmentation. CoRR Wei-I Lin, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama
2023	—	`conf`	From SMOTE to Mixup for Deep Imbalanced Classification. TAAI (1) Wei-Chao Cheng, Tan-Ha Mai, Hsuan-Tien Lin
2023	J	`jnl`	From SMOTE to Mixup for Deep Imbalanced Classification. CoRR Wei-Chao Cheng, Tan-Ha Mai, Hsuan-Tien Lin
2023	J	`jnl`	Learning key steps to attack deep reinforcement learning agents. Mach. Learn. Chien-Min Yu, Ming-Hsin Chen, Hsuan-Tien Lin
2023	J	`jnl`	Re-Benchmarking Pool-Based Active Learning for Binary Classification. CoRR Po-Yi Lu, Chun-Liang Li, Hsuan-Tien Lin
2023	—	`conf`	Reduction from Complementary-Label Learning to Probability Estimates. PAKDD (2) Wei-I Lin, Hsuan-Tien Lin
2023	J	`jnl`	SUNY: A Visual Interpretation Framework for Convolutional Neural Networks from a Necessary and Sufficient Perspective. CoRR Xiwei Xuan, Ziquan Deng, Hsuan-Tien Lin, Zhaodan Kong, Kwan-Liu Ma
2023	J	`jnl`	Score-based Conditional Generation with Fewer Labeled Data by Self-calibrating Classifier Guidance. CoRR Paul Kuo-Ming Huang, Si-An Chen, Hsuan-Tien Lin
2023	A*	`conf`	Semi-Supervised Domain Adaptation with Source Label Adaptation. CVPR Yu-Chu Yu, Hsuan-Tien Lin
2023	J	`jnl`	Semi-Supervised Domain Adaptation with Source Label Adaptation. CoRR Yu-Chu Yu, Hsuan-Tien Lin
2023	J	`jnl`	Understanding and Mitigating Spurious Correlations in Text Classification. CoRR Oscar Chew, Kuan-Hao Huang, Kai-Wei Chang, Hsuan-Tien Lin
2022	—	`conf`	Even the Simplest Baseline Needs Careful Re-investigation: A Case Study on XML-CNN. NAACL-HLT Si-An Chen, Jie-Jyun Liu, Tsung-Han Yang, Hsuan-Tien Lin, Chih-Jen Lin
2022	—	`conf`	Improving Clustering Uncertainty-weighted Embeddings for Active Domain Adaptation. TAAI Sheng-Feng Wu, Hsuan-Tien Lin
2022	J	`jnl`	Reducing Training Sample Memorization in GANs by Training with Memorization Rejection. CoRR Andrew Bai, Cho-Jui Hsieh, Wendy Chi-wen Kan, Hsuan-Tien Lin
2022	J	`jnl`	Reduction from Complementary-Label Learning to Probability Estimates. CoRR Wei-I Lin, Hsuan-Tien Lin
2021	A	`conf`	360-Degree Gaze Estimation in the Wild Using Multiple Zoom Scales. BMVC Ashesh, Chu-Song Chen, Hsuan-Tien Lin
2021	A*	`conf`	A Unified View of cGANs with and without Classifiers. NeurIPS Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin
2021	J	`jnl`	A Unified View of cGANs with and without Classifiers. CoRR Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin
2021	J	`jnl`	Accurate and Clear Precipitation Nowcasting with Consecutive Attention and Rain-map Discrimination. CoRR Ashesh, Buo-Fu Chen, Treng-Shi Huang, Boyo Chen, Chia-Tung Chang, Hsuan-Tien Lin
2021	J	`jnl`	Active Refinement for Multi-Label Learning: A Pseudo-Label Approach. CoRR Cheng-Yu Hsieh, Wei-I Lin, Miao Xu, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama
2021	A*	`conf`	Adaptive and Generative Zero-Shot Learning. ICLR Yu-Ying Chou, Hsuan-Tien Lin, Tyng-Luh Liu
2021	J	`jnl`	Improving Model Compatibility of Generative Adversarial Networks by Boundary Calibration. CoRR Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin
2021	A*	`conf`	On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition. KDD Ching-Yuan Bai, Hsuan-Tien Lin, Colin Raffel, Wendy Chi-wen Kan
2021	J	`jnl`	On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition. CoRR Ching-Yuan Bai, Hsuan-Tien Lin, Colin Raffel, Wendy Chih-wen Kan
2020	J	`jnl`	360-Degree Gaze Estimation in the Wild Using Multiple Zoom Scales. CoRR Ashesh Mishra, Hsuan-Tien Lin
2020	J	`jnl`	Active deep Q-learning with demonstration. Mach. Learn. Si-An Chen, Voot Tangkaratt, Hsuan-Tien Lin, Masashi Sugiyama
2020	A*	`ed.`	Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual. NeurIPS Hugo Larochelle, Marc'Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, Hsuan-Tien Lin
2020	—	`conf`	Benchmarking Tropical Cyclone Rapid Intensification with Satellite Images and Attention-Based Deep Models. ECML/PKDD (4) Ching-Yuan Bai, Buo-Fu Chen, Hsuan-Tien Lin
2020	—	`conf`	Cold-start Active Learning through Self-supervised Language Modeling. EMNLP (1) Michelle Yuan, Hsuan-Tien Lin, Jordan L. Boyd-Graber
2020	J	`jnl`	Cold-start Active Learning through Self-supervised Language Modeling. CoRR Michelle Yuan, Hsuan-Tien Lin, Jordan L. Boyd-Graber
2020	—	`conf`	Cost Learning Network for Imbalanced Classification. TAAI Chun-Yi Tu, Hsuan-Tien Lin
2020	—	`conf`	Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation. TAAI Yu-An Chung, Shao-Wen Yang, Hsuan-Tien Lin
2020	—	`conf`	Improving Unsupervised Domain Adaptation with Representative Selection Techniques. IAL@PKDD/ECML I-Ting Chen, Hsuan-Tien Lin
2020	C	`conf`	Learning from Label Proportions with Consistency Regularization. ACML Kuen-Han Tsai, Hsuan-Tien Lin
2020	A	`conf`	SERIL: Noise Adaptive Speech Enhancement Using Regularization-Based Incremental Learning. INTERSPEECH Chi-Chang Lee, Yu-Chen Lin, Hsuan-Tien Lin, Hsin-Min Wang, Yu Tsao
2020	J	`jnl`	SERIL: Noise Adaptive Speech Enhancement using Regularization-based Incremental Learning. CoRR Chi-Chang Lee, Yu-Chen Lin, Hsuan-Tien Lin, Hsin-Min Wang, Yu Tsao
2020	A*	`conf`	Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels. ICML Yu-Ting Chou, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama
2020	J	`jnl`	Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels. CoRR Yu-Ting Chou, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama
2019	A*	`conf`	Advances in Cost-sensitive Multiclass and Multilabel Classification. KDD Hsuan-Tien Lin
2019	J	`jnl`	Annotation cost-sensitive active learning by tree sampling. Mach. Learn. Yu-Lin Tsou, Hsuan-Tien Lin
2019	—	`conf`	Attention-based Deep Tropical Cyclone Rapid Intensification Prediction. MACLEAN@PKDD/ECML Ching-Yuan Bai, Buo-Fu Chen, Hsuan-Tien Lin
2019	J	`jnl`	Attention-based Deep Tropical Cyclone Rapid Intensification Prediction. CoRR Ching-Yuan Bai, Buo-Fu Chen, Hsuan-Tien Lin
2019	C	`conf`	Deep Learning with a Rethinking Structure for Multi-label Classification. ACML Yao-Yuan Yang, Yi-An Lin, Hong-Min Chu, Hsuan-Tien Lin
2019	J	`jnl`	Dynamic principal projection for cost-sensitive online multi-label classification. Mach. Learn. Hong-Min Chu, Kuan-Hao Huang, Hsuan-Tien Lin
2019	J	`jnl`	Learning from Label Proportions with Consistency Regularization. CoRR Kuen-Han Tsai, Hsuan-Tien Lin
2018	A*	`conf`	A Deep Model With Local Surrogate Loss for General Cost-Sensitive Multi-Label Learning. AAAI Cheng-Yu Hsieh, Yi-An Lin, Hsuan-Tien Lin
2018	J	`jnl`	Active Deep Q-learning with Demonstration. CoRR Si-An Chen, Voot Tangkaratt, Hsuan-Tien Lin, Masashi Sugiyama
2018	J	`jnl`	Automatic Bridge Bidding Using Deep Reinforcement Learning. IEEE Trans. Games Chih-Kuan Yeh, Cheng-Yu Hsieh, Hsuan-Tien Lin
2018	A*	`conf`	Compatibility Family Learning for Item Recommendation and Generation. AAAI Yong-Siang Shih, Kai-Yueh Chang, Hsuan-Tien Lin, Min Sun
2018	—	`conf`	Cost-Sensitive Reference Pair Encoding for Multi-Label Learning. PAKDD (1) Yao-Yuan Yang, Kuan-Hao Huang, Chih-Wei Chang, Hsuan-Tien Lin
2018	J	`jnl`	Deep Learning with a Rethinking Structure for Multi-label Classification. CoRR Yao-Yuan Yang, Yi-An Lin, Hong-Min Chu, Hsuan-Tien Lin
2018	—	`conf`	Multi-Label Classification with Feature-Aware Cost-Sensitive Label Embedding. TAAI Hsien-Chun Chiu, Hsuan-Tien Lin
2018	A*	`conf`	REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis. NeurIPS Yu-Shao Peng, Kai-Fu Tang, Hsuan-Tien Lin, Edward Y. Chang
2018	A*	`conf`	Rotation-blended CNNs on a New Open Dataset for Tropical Cyclone Image-to-intensity Regression. KDD Boyo Chen, Buo-Fu Chen, Hsuan-Tien Lin
2017	J	`jnl`	Active Sampling of Pairs and Points for Large-scale Linear Bipartite Ranking. CoRR Wei-Yuan Shen, Hsuan-Tien Lin
2017	J	`jnl`	Compatibility Family Learning for Item Recommendation and Generation. CoRR Yong-Siang Shih, Kai-Yueh Chang, Hsuan-Tien Lin, Min Sun
2017	—	`conf`	Cost-Sensitive Encoding for Label Space Dimension Reduction Algorithms on Multi-label Classification. TAAI Kuo-Hsuan Lo, Hsuan-Tien Lin
2017	J	`jnl`	Cost-sensitive label embedding for multi-label classification. Mach. Learn. Kuan-Hao Huang, Hsuan-Tien Lin
2017	B	`conf`	Cyclic Classifier Chain for Cost-Sensitive Multilabel Classification. DSAA Yi-An Lin, Hsuan-Tien Lin
2017	J	`jnl`	Dynamic Principal Projection for Cost-Sensitive Online Multi-Label Classification. CoRR Hong-Min Chu, Kuan-Hao Huang, Hsuan-Tien Lin
2017	J	`jnl`	Progressive random k-labelsets for cost-sensitive multi-label classification. Mach. Learn. Yuping Wu, Hsuan-Tien Lin
2017	J	`jnl`	Soft Methodology for Cost-and-error Sensitive Classification. CoRR Te-Kang Jan, Da-Wei Wang, Chi-Hung Lin, Hsuan-Tien Lin
2017	J	`jnl`	libact: Pool-based Active Learning in Python. CoRR Yao-Yuan Yang, Shao-Chuan Lee, Yu-An Chung, Tung-En Wu, Si-An Chen, Hsuan-Tien Lin
2016	A*	`conf`	A Novel Uncertainty Sampling Algorithm for Cost-Sensitive Multiclass Active Learning. ICDM Kuan-Hao Huang, Hsuan-Tien Lin
2016	—	`conf`	A Simple Unlearning Framework for Online Learning Under Concept Drifts. PAKDD (1) Sheng-Chi You, Hsuan-Tien Lin
2016	A	`conf`	Automatic Bridge Bidding Using Deep Reinforcement Learning. ECAI Chih-Kuan Yeh, Hsuan-Tien Lin
2016	J	`jnl`	Automatic Bridge Bidding Using Deep Reinforcement Learning. CoRR Chih-Kuan Yeh, Hsuan-Tien Lin
2016	A*	`conf`	Can Active Learning Experience Be Transferred? ICDM Hong-Min Chu, Hsuan-Tien Lin
2016	J	`jnl`	Can Active Learning Experience Be Transferred? CoRR Hong-Min Chu, Hsuan-Tien Lin
2016	A*	`conf`	Cost-Aware Pre-Training for Multiclass Cost-Sensitive Deep Learning. IJCAI Yu-An Chung, Hsuan-Tien Lin, Shao-Wen Yang
2016	J	`jnl`	Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation. CoRR Yu-An Chung, Hsuan-Tien Lin
2016	J	`jnl`	Cost-Sensitive Random Pair Encoding for Multi-Label Classification. CoRR Yao-Yuan Yang, Chih-Wei Chang, Hsuan-Tien Lin
2016	J	`jnl`	Cost-sensitive Label Embedding for Multi-label Classification. CoRR Kuan-Hao Huang, Hsuan-Tien Lin
2016	—	`conf`	Linear Upper Confidence Bound Algorithm for Contextual Bandit Problem with Piled Rewards. PAKDD (2) Kuan-Hao Huang, Hsuan-Tien Lin
2016	A	`conf`	Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA. AISTATS Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu
2015	—	`conf`	A practical divide-and-conquer approach for preference-based learning to rank. TAAI Han-Jay Yang, Hsuan-Tien Lin
2015	J	`jnl`	Active Learning Using Hint Information. Neural Comput. Chun-Liang Li, Chun-Sung Ferng, Hsuan-Tien Lin
2015	A*	`conf`	Active Learning by Learning. AAAI Wei-Ning Hsu, Hsuan-Tien Lin
2015	J	`jnl`	Combination of feature engineering and ranking models for paper-author identification in KDD cup 2013. J. Mach. Learn. Res. 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
2015	—	`conf`	Contract Bridge Bidding by Learning. AAAI Workshop: Computer Poker and Imperfect Information Chun-Yen Ho, Hsuan-Tien Lin
2015	J	`jnl`	Cost-aware Pre-training for Multiclass Cost-sensitive Deep Learning. CoRR Yu-An Chung, Hsuan-Tien Lin, Shao-Wen Yang
2015	J	`jnl`	Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA. CoRR Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu
2014	A*	`conf`	Boosting with Online Binary Learners for the Multiclass Bandit Problem. ICML Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu
2014	A*	`conf`	Condensed Filter Tree for Cost-Sensitive Multi-Label Classification. ICML Chun-Liang Li, Hsuan-Tien Lin
2014	J	`jnl`	Effective string processing and matching for author disambiguation. J. Mach. Learn. Res. 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
2014	J	`jnl`	Improving ranking performance with cost-sensitive ordinal classification via regression. Inf. Retr. Yu-Xun Ruan, Hsuan-Tien Lin, Ming-Feng Tsai
2014	—	`conf`	Machine Learning Approaches for Interactive Verification. PAKDD (2) Yu-Cheng Chou, Hsuan-Tien Lin
2014	C	`conf`	Pseudo-reward Algorithms for Contextual Bandits with Linear Payoff Functions. ACML Ku-Chun Chou, Hsuan-Tien Lin, Chao-Kai Chiang, Chi-Jen Lu
2014	C	`conf`	Reduction from Cost-Sensitive Multiclass Classification to One-versus-One Binary Classification. ACML Hsuan-Tien Lin
2013	—	`conf`	Active Learning for Multiclass Cost-Sensitive Classification Using Probabilistic Models. TAAI Po-Lung Chen, Hsuan-Tien Lin
2013	C	`conf`	Active Sampling of Pairs and Points for Large-scale Linear Bipartite Ranking. ACML Wei-Yuan Shen, Hsuan-Tien Lin
2013	—	`conf`	Combination of feature engineering and ranking models for paper-author identification in KDD Cup 2013. KDD Cup 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
2013	—	`conf`	Data Selection Techniques for Large-Scale Rank SVM. TAAI Ken-Yi Lin, Te-Kang Jan, Hsuan-Tien Lin
2013	—	`conf`	Effective string processing and matching for author disambiguation. KDD Cup 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	J	`jnl`	Multilabel Classification Using Error-Correcting Codes of Hard or Soft Bits. IEEE Trans. Neural Networks Learn. Syst. Chun-Sung Ferng, Hsuan-Tien Lin
2013	—	`conf`	Pairwise Regression with Upper Confidence Bound for Contextual Bandit with Multiple Actions. TAAI Ya-Hsuan Chang, Hsuan-Tien Lin
2012	—	`conf`	A Linear Ensemble of Individual and Blended Models for Music Rating Prediction. KDD Cup Po-Lung Chen, Chen-Tse Tsai, Yao-Nan Chen, Ku-Chun Chou, Chun-Liang Li, Cheng-Hao Tsai, Kuan-Wei Wu, Yu-Cheng Chou, Chung-Yi Li, Wei-Shih Lin, Shu-Hao Yu, Rong-Bing Chiu, Chieh-Yen Lin, Chien-Chih Wang, Po-Wei Wang, Wei-Lun Su, Chen-Hung Wu, Tsung-Ting Kuo, Todd G. McKenzie, Ya-Hsuan Chang, Chun-Sung Ferng, Chia-Mau Ni, Hsuan-Tien Lin, Chih-Jen Lin, Shou-De Lin
2012	A*	`conf`	A simple methodology for soft cost-sensitive classification. KDD Te-Kang Jan, Da-Wei Wang, Chi-Hung Lin, Hsuan-Tien Lin
2012	C	`conf`	Active Learning with Hinted Support Vector Machine. ACML Chun-Liang Li, Chun-Sung Ferng, Hsuan-Tien Lin
2012	A*	`conf`	An Online Boosting Algorithm with Theoretical Justifications. ICML Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu
2012	—	`conf`	Feature-aware Label Space Dimension Reduction for Multi-label Classification. NIPS Yao-Nan Chen, Hsuan-Tien Lin
2012	J	`jnl`	Multilabel Classification with Principal Label Space Transformation. Neural Comput. Farbound Tai, Hsuan-Tien Lin
2012	—	`conf`	Novel Models and Ensemble Techniques to Discriminate Favorite Items from Unrated Ones for Personalized Music Recommendation. KDD Cup Todd G. McKenzie, Chun-Sung Ferng, Yao-Nan Chen, Chun-Liang Li, Cheng-Hao Tsai, Kuan-Wei Wu, Ya-Hsuan Chang, Chung-Yi Li, Wei-Shih Lin, Shu-Hao Yu, Chieh-Yen Lin, Po-Wei Wang, Chia-Mau Ni, Wei-Lun Su, Tsung-Ting Kuo, Chen-Tse Tsai, Po-Lung Chen, Rong-Bing Chiu, Ku-Chun Chou, Yu-Cheng Chou, Chien-Chih Wang, Chen-Hung Wu, Hsuan-Tien Lin, Chih-Jen Lin, Shou-De Lin
2012	J	`jnl`	Reduction from Cost-Sensitive Ordinal Ranking to Weighted Binary Classification. Neural Comput. Hsuan-Tien Lin, Ling Li
2012	J	`jnl`	Unsupervised Semantic Feature Discovery for Image Object Retrieval and Tag Refinement. IEEE Trans. Multim. Yin-Hsi Kuo, Wen-Huang Cheng, Hsuan-Tien Lin, Winston H. Hsu
2011	—	`conf`	Cost-Sensitive Classification on Pathogen Species of Bacterial Meningitis by Surface Enhanced Raman Scattering. BIBM Te-Kang Jan, Hsuan-Tien Lin, Hsin-Pai Chen, Tsung-Chen Chern, Chung-Yueh Huang, Bing-Cheng Wen, Chia-Wen Chung, Yung-Jui Li, Ya-Ching Chuang, Li-li Li, Yu-Jiun Chan, Juen-Kai Wang, Yuh-Lin Wang, Chi-Hung Lin, Da-Wei Wang
2011	C	`conf`	Multi-label Active Learning with Auxiliary Learner. ACML Chen-Wei Hung, Hsuan-Tien Lin
2011	C	`conf`	Multi-label Classification with Error-correcting Codes. ACML Chun-Sung Ferng, Hsuan-Tien Lin
2011	A*	`conf`	Unsupervised auxiliary visual words discovery for large-scale image object retrieval. CVPR Yin-Hsi Kuo, Hsuan-Tien Lin, Wen-Huang Cheng, Yi-Hsuan Yang, Winston H. Hsu
2010	A*	`conf`	One-sided Support Vector Regression for Multiclass Cost-sensitive Classification. ICML Han-Hsing Tu, Hsuan-Tien Lin
2009	—	`conf`	An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naive Bayes. KDD Cup Hung-Yi Lo, Kai-Wei Chang, Shang-Tse Chen, Tsung-Hsien Chiang, Chun-Sung Ferng, Cho-Jui Hsieh, Yi-Kuang Ko, Tsung-Ting Kuo, Hung-Che Lai, Ken-Yi Lin, Chia-Hsuan Wang, Hsiang-Fu Yu, Chih-Jen Lin, Hsuan-Tien Lin, Shou-De Lin
2008	—	`—`	From Ordinal Ranking to Binary Classification. Hsuan-Tien Lin
2008	J	`jnl`	Support Vector Machinery for Infinite Ensemble Learning. J. Mach. Learn. Res. Hsuan-Tien Lin, Ling Li
2007	J	`jnl`	A note on Platt's probabilistic outputs for support vector machines. Mach. Learn. Hsuan-Tien Lin, Chih-Jen Lin, Ruby C. Weng
2007	B	`conf`	Optimizing 0/1 Loss for Perceptrons by Random Coordinate Descent. IJCNN Ling Li, Hsuan-Tien Lin
2006	B	`conf`	Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice. ALT Hsuan-Tien Lin, Ling Li
2006	—	`conf`	Ordinal Regression by Extended Binary Classification. NIPS Ling Li, Hsuan-Tien Lin
2005	—	`conf`	Improving Generalization by Data Categorization. PKDD Ling Li, Amrit Pratap, Hsuan-Tien Lin, Yaser S. Abu-Mostafa
2005	—	`conf`	Infinite Ensemble Learning with Support Vector Machines. ECML Hsuan-Tien Lin, Ling Li
2002	J	`jnl`	A Note on the Decomposition Methods for Support Vector Regression. Neural Comput. Shuo-Peng Liao, Hsuan-Tien Lin, Chih-Jen Lin