default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDHsuan-Tien Lin
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[c69]Vo Nguyen Le Duy, Hsuan-Tien Lin, Ichiro Takeuchi:
CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference. AISTATS 2024: 1828-1836- [c68]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: 1013-1025 - [c67]Xiwei Xuan
, Ziquan Deng, Hsuan-Tien Lin, Kwan-Liu Ma:
SLIM: Spuriousness Mitigation with Minimal Human Annotations. ECCV (46) 2024: 215-231 - [i38]Xiwei Xuan, Ziquan Deng, Hsuan-Tien Lin, Kwan-Liu Ma:
SLIM: Spuriousness Mitigation with Minimal Human Annotations. CoRR abs/2407.05594 (2024) - [i37]Oscar Chew, Po-Yi Lu, Jayden Lin, Hsuan-Tien Lin:
Defending Text-to-image Diffusion Models: Surprising Efficacy of Textual Perturbations Against Backdoor Attacks. CoRR abs/2408.15721 (2024) - 2023
- [j18]Chien-Min Yu, Ming-Hsin Chen, Hsuan-Tien Lin:
Learning key steps to attack deep reinforcement learning agents. Mach. Learn. 112(5): 1499-1522 (2023) - [c66]Yu-Chu Yu, Hsuan-Tien Lin:
Semi-Supervised Domain Adaptation with Source Label Adaptation. CVPR 2023: 24100-24109 - [c65]Wei-I Lin, Hsuan-Tien Lin:
Reduction from Complementary-Label Learning to Probability Estimates. PAKDD (2) 2023: 469-481 - [c64]Wei-Chao Cheng, Tan-Ha Mai, Hsuan-Tien Lin:
From SMOTE to Mixup for Deep Imbalanced Classification. TAAI (1) 2023: 75-96 - [i36]Yu-Chu Yu, Hsuan-Tien Lin:
Semi-Supervised Domain Adaptation with Source Label Adaptation. CoRR abs/2302.02335 (2023) - [i35]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 abs/2303.00244 (2023) - [i34]Hsiu-Hsuan Wang, Wei-I Lin, Hsuan-Tien Lin:
CLCIFAR: CIFAR-Derived Benchmark Datasets with Human Annotated Complementary Labels. CoRR abs/2305.08295 (2023) - [i33]Wei-I Lin, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama:
Enhancing Label Sharing Efficiency in Complementary-Label Learning with Label Augmentation. CoRR abs/2305.08344 (2023) - [i32]Oscar Chew, Kuan-Hao Huang, Kai-Wei Chang, Hsuan-Tien Lin:
Understanding and Mitigating Spurious Correlations in Text Classification. CoRR abs/2305.13654 (2023) - [i31]Po-Yi Lu, Chun-Liang Li, Hsuan-Tien Lin:
Re-Benchmarking Pool-Based Active Learning for Binary Classification. CoRR abs/2306.08954 (2023) - [i30]Paul Kuo-Ming Huang, Si-An Chen, Hsuan-Tien Lin:
Score-based Conditional Generation with Fewer Labeled Data by Self-calibrating Classifier Guidance. CoRR abs/2307.04081 (2023) - [i29]Wei-Chao Cheng, Tan-Ha Mai, Hsuan-Tien Lin:
From SMOTE to Mixup for Deep Imbalanced Classification. CoRR abs/2308.15457 (2023) - [i28]Vo Nguyen Le Duy, Hsuan-Tien Lin, Ichiro Takeuchi:
CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference. CoRR abs/2310.14608 (2023) - 2022
- [c63]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: 1987-2000 - [c62]Sheng-Feng Wu, Hsuan-Tien Lin:
Improving Clustering Uncertainty-weighted Embeddings for Active Domain Adaptation. TAAI 2022: 18-23 - [i27]Wei-I Lin, Hsuan-Tien Lin:
Reduction from Complementary-Label Learning to Probability Estimates. CoRR abs/2209.09500 (2022) - [i26]Andrew Bai, Cho-Jui Hsieh, Wendy Chi-wen Kan, Hsuan-Tien Lin:
Reducing Training Sample Memorization in GANs by Training with Memorization Rejection. CoRR abs/2210.12231 (2022) - 2021
- [c61]Ashesh, Chu-Song Chen, Hsuan-Tien Lin:
360-Degree Gaze Estimation in the Wild Using Multiple Zoom Scales. BMVC 2021: 372 - [c60]Yu-Ying Chou, Hsuan-Tien Lin, Tyng-Luh Liu:
Adaptive and Generative Zero-Shot Learning. ICLR 2021 - [c59]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: 2534-2542 - [c58]Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin:
A Unified View of cGANs with and without Classifiers. NeurIPS 2021: 27566-27579 - [i25]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 abs/2102.08175 (2021) - [i24]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 abs/2106.03062 (2021) - [i23]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 abs/2109.14676 (2021) - [i22]Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin:
A Unified View of cGANs with and without Classifiers. CoRR abs/2111.01035 (2021) - [i21]Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin:
Improving Model Compatibility of Generative Adversarial Networks by Boundary Calibration. CoRR abs/2111.02316 (2021) - 2020
- [j17]Si-An Chen, Voot Tangkaratt, Hsuan-Tien Lin, Masashi Sugiyama:
Active deep Q-learning with demonstration. Mach. Learn. 109(9-10): 1699-1725 (2020) - [c57]Kuen-Han Tsai, Hsuan-Tien Lin:
Learning from Label Proportions with Consistency Regularization. ACML 2020: 513-528 - [c56]Michelle Yuan, Hsuan-Tien Lin, Jordan L. Boyd-Graber:
Cold-start Active Learning through Self-supervised Language Modeling. EMNLP (1) 2020: 7935-7948 - [c55]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: 1929-1938 - [c54]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: 2432-2436 - [c53]I-Ting Chen, Hsuan-Tien Lin:
Improving Unsupervised Domain Adaptation with Representative Selection Techniques. IAL@PKDD/ECML 2020: 5-21 - [c52]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: 497-512 - [c51]Chun-Yi Tu, Hsuan-Tien Lin:
Cost Learning Network for Imbalanced Classification. TAAI 2020: 47-51 - [c50]Yu-An Chung, Shao-Wen Yang, Hsuan-Tien Lin:
Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation. TAAI 2020: 108-113 - [e1]Hugo Larochelle, Marc'Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, Hsuan-Tien Lin:
Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual. 2020 [contents] - [i20]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 abs/2005.11760 (2020) - [i19]Yu-Ting Chou, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama:
Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels. CoRR abs/2007.02235 (2020) - [i18]Ashesh Mishra, Hsuan-Tien Lin:
360-Degree Gaze Estimation in the Wild Using Multiple Zoom Scales. CoRR abs/2009.06924 (2020) - [i17]Michelle Yuan, Hsuan-Tien Lin, Jordan L. Boyd-Graber:
Cold-start Active Learning through Self-supervised Language Modeling. CoRR abs/2010.09535 (2020)
2010 – 2019
- 2019
- [j16]Yu-Lin Tsou, Hsuan-Tien Lin:
Annotation cost-sensitive active learning by tree sampling. Mach. Learn. 108(5): 785-807 (2019) - [j15]Hong-Min Chu, Kuan-Hao Huang, Hsuan-Tien Lin:
Dynamic principal projection for cost-sensitive online multi-label classification. Mach. Learn. 108(8-9): 1193-1230 (2019) - [c49]Yao-Yuan Yang, Yi-An Lin, Hong-Min Chu, Hsuan-Tien Lin:
Deep Learning with a Rethinking Structure for Multi-label Classification. ACML 2019: 125-140 - [c48]Hsuan-Tien Lin:
Advances in Cost-sensitive Multiclass and Multilabel Classification. KDD 2019: 3187-3188 - [c47]Ching-Yuan Bai, Buo-Fu Chen, Hsuan-Tien Lin:
Attention-based Deep Tropical Cyclone Rapid Intensification Prediction. MACLEAN@PKDD/ECML 2019 - [i16]Ching-Yuan Bai, Buo-Fu Chen, Hsuan-Tien Lin:
Attention-based Deep Tropical Cyclone Rapid Intensification Prediction. CoRR abs/1909.11616 (2019) - [i15]Kuen-Han Tsai, Hsuan-Tien Lin:
Learning from Label Proportions with Consistency Regularization. CoRR abs/1910.13188 (2019) - 2018
- [j14]Chih-Kuan Yeh, Cheng-Yu Hsieh, Hsuan-Tien Lin:
Automatic Bridge Bidding Using Deep Reinforcement Learning. IEEE Trans. Games 10(4): 365-377 (2018) - [c46]Yong-Siang Shih, Kai-Yueh Chang, Hsuan-Tien Lin, Min Sun:
Compatibility Family Learning for Item Recommendation and Generation. AAAI 2018: 2403-2410 - [c45]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: 3239-3246 - [c44]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: 90-99 - [c43]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: 7333-7342 - [c42]Yao-Yuan Yang, Kuan-Hao Huang, Chih-Wei Chang, Hsuan-Tien Lin:
Cost-Sensitive Reference Pair Encoding for Multi-Label Learning. PAKDD (1) 2018: 143-155 - [c41]Hsien-Chun Chiu, Hsuan-Tien Lin:
Multi-Label Classification with Feature-Aware Cost-Sensitive Label Embedding. TAAI 2018: 40-45 - [i14]Yao-Yuan Yang, Yi-An Lin, Hong-Min Chu, Hsuan-Tien Lin:
Deep Learning with a Rethinking Structure for Multi-label Classification. CoRR abs/1802.01697 (2018) - [i13]Si-An Chen, Voot Tangkaratt, Hsuan-Tien Lin, Masashi Sugiyama:
Active Deep Q-learning with Demonstration. CoRR abs/1812.02632 (2018) - 2017
- [j13]Yuping Wu, Hsuan-Tien Lin:
Progressive random k-labelsets for cost-sensitive multi-label classification. Mach. Learn. 106(5): 671-694 (2017) - [j12]Kuan-Hao Huang, Hsuan-Tien Lin:
Cost-sensitive label embedding for multi-label classification. Mach. Learn. 106(9-10): 1725-1746 (2017) - [c40]Yi-An Lin, Hsuan-Tien Lin:
Cyclic Classifier Chain for Cost-Sensitive Multilabel Classification. DSAA 2017: 11-20 - [c39]Kuo-Hsuan Lo, Hsuan-Tien Lin:
Cost-Sensitive Encoding for Label Space Dimension Reduction Algorithms on Multi-label Classification. TAAI 2017: 136-141 - [i12]Wei-Yuan Shen, Hsuan-Tien Lin:
Active Sampling of Pairs and Points for Large-scale Linear Bipartite Ranking. CoRR abs/1708.07336 (2017) - [i11]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 abs/1710.00379 (2017) - [i10]Te-Kang Jan, Da-Wei Wang, Chi-Hung Lin, Hsuan-Tien Lin:
Soft Methodology for Cost-and-error Sensitive Classification. CoRR abs/1710.09515 (2017) - [i9]Hong-Min Chu, Kuan-Hao Huang, Hsuan-Tien Lin:
Dynamic Principal Projection for Cost-Sensitive Online Multi-Label Classification. CoRR abs/1711.05060 (2017) - [i8]Yong-Siang Shih, Kai-Yueh Chang, Hsuan-Tien Lin, Min Sun:
Compatibility Family Learning for Item Recommendation and Generation. CoRR abs/1712.01262 (2017) - 2016
- [c38]Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu:
Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA. AISTATS 2016: 473-481 - [c37]Chih-Kuan Yeh, Hsuan-Tien Lin:
Automatic Bridge Bidding Using Deep Reinforcement Learning. ECAI 2016: 1362-1369 - [c36]Hong-Min Chu, Hsuan-Tien Lin:
Can Active Learning Experience Be Transferred? ICDM 2016: 841-846 - [c35]Kuan-Hao Huang, Hsuan-Tien Lin:
A Novel Uncertainty Sampling Algorithm for Cost-Sensitive Multiclass Active Learning. ICDM 2016: 925-930 - [c34]Yu-An Chung, Hsuan-Tien Lin, Shao-Wen Yang:
Cost-Aware Pre-Training for Multiclass Cost-Sensitive Deep Learning. IJCAI 2016: 1411-1417 - [c33]Sheng-Chi You, Hsuan-Tien Lin:
A Simple Unlearning Framework for Online Learning Under Concept Drifts. PAKDD (1) 2016: 115-126 - [c32]Kuan-Hao Huang, Hsuan-Tien Lin:
Linear Upper Confidence Bound Algorithm for Contextual Bandit Problem with Piled Rewards. PAKDD (2) 2016: 143-155 - [i7]Kuan-Hao Huang, Hsuan-Tien Lin:
Cost-sensitive Label Embedding for Multi-label Classification. CoRR abs/1603.09048 (2016) - [i6]Chih-Kuan Yeh, Hsuan-Tien Lin:
Automatic Bridge Bidding Using Deep Reinforcement Learning. CoRR abs/1607.03290 (2016) - [i5]Hong-Min Chu, Hsuan-Tien Lin:
Can Active Learning Experience Be Transferred? CoRR abs/1608.00667 (2016) - [i4]Yu-An Chung, Hsuan-Tien Lin:
Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation. CoRR abs/1611.05134 (2016) - [i3]Yao-Yuan Yang, Chih-Wei Chang, Hsuan-Tien Lin:
Cost-Sensitive Random Pair Encoding for Multi-Label Classification. CoRR abs/1611.09461 (2016) - 2015
- [j11]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: 2921-2947 (2015) - [j10]Chun-Liang Li, Chun-Sung Ferng, Hsuan-Tien Lin:
Active Learning Using Hint Information. Neural Comput. 27(8): 1738-1765 (2015) - [c31]Chun-Yen Ho, Hsuan-Tien Lin:
Contract Bridge Bidding by Learning. AAAI Workshop: Computer Poker and Imperfect Information 2015 - [c30]Wei-Ning Hsu, Hsuan-Tien Lin:
Active Learning by Learning. AAAI 2015: 2659-2665 - [c29]Han-Jay Yang, Hsuan-Tien Lin:
A practical divide-and-conquer approach for preference-based learning to rank. TAAI 2015: 554-561 - [i2]Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu:
Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA. CoRR abs/1506.01490 (2015) - [i1]Yu-An Chung, Hsuan-Tien Lin, Shao-Wen Yang:
Cost-aware Pre-training for Multiclass Cost-sensitive Deep Learning. CoRR abs/1511.09337 (2015) - 2014
- [j9]Yu-Xun Ruan, Hsuan-Tien Lin, Ming-Feng Tsai:
Improving ranking performance with cost-sensitive ordinal classification via regression. Inf. Retr. 17(1): 1-20 (2014) - [j8]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): 3037-3064 (2014) - [c28]Ku-Chun Chou, Hsuan-Tien Lin, Chao-Kai Chiang, Chi-Jen Lu:
Pseudo-reward Algorithms for Contextual Bandits with Linear Payoff Functions. ACML 2014 - [c27]Hsuan-Tien Lin:
Reduction from Cost-Sensitive Multiclass Classification to One-versus-One Binary Classification. ACML 2014 - [c26]Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu:
Boosting with Online Binary Learners for the Multiclass Bandit Problem. ICML 2014: 342-350 - [c25]Chun-Liang Li, Hsuan-Tien Lin:
Condensed Filter Tree for Cost-Sensitive Multi-Label Classification. ICML 2014: 423-431 - [c24]Yu-Cheng Chou, Hsuan-Tien Lin:
Machine Learning Approaches for Interactive Verification. PAKDD (2) 2014: 122-133 - 2013
- [j7]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): 1888-1900 (2013) - [c23]Wei-Yuan Shen, Hsuan-Tien Lin:
Active Sampling of Pairs and Points for Large-scale Linear Bipartite Ranking. ACML 2013: 388-403 - [c22]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: 2:1-2:7 - [c21]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: 7:1-7:9 - [c20]Po-Lung Chen, Hsuan-Tien Lin:
Active Learning for Multiclass Cost-Sensitive Classification Using Probabilistic Models. TAAI 2013: 13-18 - [c19]Ya-Hsuan Chang, Hsuan-Tien Lin:
Pairwise Regression with Upper Confidence Bound for Contextual Bandit with Multiple Actions. TAAI 2013: 19-24 - [c18]Ken-Yi Lin, Te-Kang Jan, Hsuan-Tien Lin:
Data Selection Techniques for Large-Scale Rank SVM. TAAI 2013: 25-30 - 2012
- [j6]Hsuan-Tien Lin, Ling Li:
Reduction from Cost-Sensitive Ordinal Ranking to Weighted Binary Classification. Neural Comput. 24(5): 1329-1367 (2012) - [j5]Farbound Tai, Hsuan-Tien Lin:
Multilabel Classification with Principal Label Space Transformation. Neural Comput. 24(9): 2508-2542 (2012) - [j4]Yin-Hsi Kuo, Wen-Huang Cheng, Hsuan-Tien Lin, Winston H. Hsu:
Unsupervised Semantic Feature Discovery for Image Object Retrieval and Tag Refinement. IEEE Trans. Multim. 14(4): 1079-1090 (2012) - [c17]Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu:
An Online Boosting Algorithm with Theoretical Justifications. ICML 2012 - [c16]Te-Kang Jan, Da-Wei Wang, Chi-Hung Lin, Hsuan-Tien Lin:
A simple methodology for soft cost-sensitive classification. KDD 2012: 141-149 - [c15]Yao-Nan Chen, Hsuan-Tien Lin:
Feature-aware Label Space Dimension Reduction for Multi-label Classification. NIPS 2012: 1538-1546 - [c14]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:
A Linear Ensemble of Individual and Blended Models for Music Rating Prediction. KDD Cup 2012: 21-60 - [c13]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:
Novel Models and Ensemble Techniques to Discriminate Favorite Items from Unrated Ones for Personalized Music Recommendation. KDD Cup 2012: 101-135 - [c12]Chun-Liang Li, Chun-Sung Ferng, Hsuan-Tien Lin:
Active Learning with Hinted Support Vector Machine. ACML 2012: 221-235 - 2011
- [c11]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:
Cost-Sensitive Classification on Pathogen Species of Bacterial Meningitis by Surface Enhanced Raman Scattering. BIBM 2011: 390-393 - [c10]Yin-Hsi Kuo, Hsuan-Tien Lin, Wen-Huang Cheng, Yi-Hsuan Yang, Winston H. Hsu:
Unsupervised auxiliary visual words discovery for large-scale image object retrieval. CVPR 2011: 905-912 - [c9]Chun-Sung Ferng, Hsuan-Tien Lin:
Multi-label Classification with Error-correcting Codes. ACML 2011: 281-295 - [c8]Chen-Wei Hung, Hsuan-Tien Lin:
Multi-label Active Learning with Auxiliary Learner. ACML 2011: 315-332 - 2010
- [c7]Han-Hsing Tu, Hsuan-Tien Lin:
One-sided Support Vector Regression for Multiclass Cost-sensitive Classification. ICML 2010: 1095-1102
2000 – 2009
- 2009
- [c6]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:
An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naive Bayes. KDD Cup 2009: 57-64 - 2008
- [b1]Hsuan-Tien Lin:
From Ordinal Ranking to Binary Classification. California Institute of Technology, USA, 2008 - [j3]Hsuan-Tien Lin, Ling Li:
Support Vector Machinery for Infinite Ensemble Learning. J. Mach. Learn. Res. 9: 285-312 (2008) - 2007
- [j2]Hsuan-Tien Lin, Chih-Jen Lin, Ruby C. Weng:
A note on Platt's probabilistic outputs for support vector machines. Mach. Learn. 68(3): 267-276 (2007) - [c5]Ling Li, Hsuan-Tien Lin:
Optimizing 0/1 Loss for Perceptrons by Random Coordinate Descent. IJCNN 2007: 749-754 - 2006
- [c4]Hsuan-Tien Lin, Ling Li:
Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice. ALT 2006: 319-333 - [c3]Ling Li, Hsuan-Tien Lin:
Ordinal Regression by Extended Binary Classification. NIPS 2006: 865-872 - 2005
- [c2]Hsuan-Tien Lin, Ling Li:
Infinite Ensemble Learning with Support Vector Machines. ECML 2005: 242-254 - [c1]Ling Li, Amrit Pratap, Hsuan-Tien Lin, Yaser S. Abu-Mostafa:
Improving Generalization by Data Categorization. PKDD 2005: 157-168 - 2002
- [j1]Shuo-Peng Liao, Hsuan-Tien Lin, Chih-Jen Lin:
A Note on the Decomposition Methods for Support Vector Regression. Neural Comput. 14(6): 1267-1281 (2002)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-23 20:36 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
