Hsuan-Tien Lin

According to our database, Hsuan-Tien Lin authored at least 105 papers between 2002 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

MAX: Masked Autoencoder for X-ray Fluorescence in Geological Investigation.

An-Sheng Lee, Yu-Wen Pao, Hsuan-Tien Lin, Sofia Ya Hsuan Liou

CoRR, 2024

Reducing Source-Private Bias in Extreme Universal Domain Adaptation.

Hung-Chieh Fang, Po-Yi Lu, Hsuan-Tien Lin

CoRR, 2024

TableRAG: Million-Token Table Understanding with Language Models.

Si-An Chen, Lesly Miculicich, Julian Martin Eisenschlos, Zifeng Wang, Zilong Wang, Yanfei Chen, Yasuhisa Fujii, Hsuan-Tien Lin, Chen-Yu Lee, Tomas Pfister

CoRR, 2024

Defending Text-to-image Diffusion Models: Surprising Efficacy of Textual Perturbations Against Backdoor Attacks.

Oscar Chew, Po-Yi Lu, Jayden Lin, Hsuan-Tien Lin

CoRR, 2024

SLIM: Spuriousness Mitigation with Minimal Human Annotations.

Xiwei Xuan, Ziquan Deng, Hsuan-Tien Lin, Kwan-Liu Ma

Proceedings of the Computer Vision - ECCV 2024, 2024

Understanding and Mitigating Spurious Correlations in Text Classification with Neighborhood Analysis.

Oscar Chew, Hsuan-Tien Lin, Kai-Wei Chang, Kuan-Hao Huang

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference.

Vo Nguyen Le Duy, Hsuan-Tien Lin, Ichiro Takeuchi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Learning key steps to attack deep reinforcement learning agents.

Chien-Min Yu, Ming-Hsin Chen, Hsuan-Tien Lin

Mach. Learn., May, 2023

Score-based Conditional Generation with Fewer Labeled Data by Self-calibrating Classifier Guidance.

Paul Kuo-Ming Huang, Si-An Chen, Hsuan-Tien Lin

CoRR, 2023

Re-Benchmarking Pool-Based Active Learning for Binary Classification.

Po-Yi Lu, Chun-Liang Li, Hsuan-Tien Lin

CoRR, 2023

Understanding and Mitigating Spurious Correlations in Text Classification.

Oscar Chew, Kuan-Hao Huang, Kai-Wei Chang, Hsuan-Tien Lin

CoRR, 2023

Enhancing Label Sharing Efficiency in Complementary-Label Learning with Label Augmentation.

Wei-I Lin, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama

CoRR, 2023

CLCIFAR: CIFAR-Derived Benchmark Datasets with Human Annotated Complementary Labels.

Hsiu-Hsuan Wang, Wei-I Lin, Hsuan-Tien Lin

CoRR, 2023

SUNY: A Visual Interpretation Framework for Convolutional Neural Networks from a Necessary and Sufficient Perspective.

Xiwei Xuan, Ziquan Deng, Hsuan-Tien Lin, Zhaodan Kong, Kwan-Liu Ma

CoRR, 2023

From SMOTE to Mixup for Deep Imbalanced Classification.

Wei-Chao Cheng, Tan-Ha Mai, Hsuan-Tien Lin

Proceedings of the Technologies and Applications of Artificial Intelligence, 2023

Reduction from Complementary-Label Learning to Probability Estimates.

Wei-I Lin, Hsuan-Tien Lin

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Semi-Supervised Domain Adaptation with Source Label Adaptation.

Yu-Chu Yu, Hsuan-Tien Lin

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Reducing Training Sample Memorization in GANs by Training with Memorization Rejection.

Andrew Bai, Cho-Jui Hsieh, Wendy Chi-wen Kan, Hsuan-Tien Lin

CoRR, 2022

Improving Clustering Uncertainty-weighted Embeddings for Active Domain Adaptation.

Sheng-Feng Wu, Hsuan-Tien Lin

Proceedings of the International Conference on Technologies and Applications of Artificial Intelligence, 2022

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

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

2021

Improving Model Compatibility of Generative Adversarial Networks by Boundary Calibration.

Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin

CoRR, 2021

Active Refinement for Multi-Label Learning: A Pseudo-Label Approach.

Cheng-Yu Hsieh, Wei-I Lin, Miao Xu, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama

CoRR, 2021

Accurate and Clear Precipitation Nowcasting with Consecutive Attention and Rain-map Discrimination.

Ashesh, Buo-Fu Chen, Treng-Shi Huang, Boyo Chen, Chia-Tung Chang, Hsuan-Tien Lin

CoRR, 2021

A Unified View of cGANs with and without Classifiers.

Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Adaptive and Generative Zero-Shot Learning.

Yu-Ying Chou, Hsuan-Tien Lin, Tyng-Luh Liu

Proceedings of the 9th International Conference on Learning Representations, 2021

360-Degree Gaze Estimation in the Wild Using Multiple Zoom Scales.

Ashesh, Chu-Song Chen, Hsuan-Tien Lin

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020

Active deep Q-learning with demonstration.

Si-An Chen, Voot Tangkaratt, Hsuan-Tien Lin, Masashi Sugiyama

Mach. Learn., 2020

360-Degree Gaze Estimation in the Wild Using Multiple Zoom Scales.

Ashesh Mishra, Hsuan-Tien Lin

CoRR, 2020

Cost Learning Network for Imbalanced Classification.

Chun-Yi Tu, Hsuan-Tien Lin

Proceedings of the International Conference on Technologies and Applications of Artificial Intelligence, 2020

Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation.

Yu-An Chung, Shao-Wen Yang, Hsuan-Tien Lin

Proceedings of the International Conference on Technologies and Applications of Artificial Intelligence, 2020

Improving Unsupervised Domain Adaptation with Representative Selection Techniques.

I-Ting Chen, Hsuan-Tien Lin

Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2020), 2020

Benchmarking Tropical Cyclone Rapid Intensification with Satellite Images and Attention-Based Deep Models.

Ching-Yuan Bai, Buo-Fu Chen, Hsuan-Tien Lin

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track, 2020

SERIL: Noise Adaptive Speech Enhancement Using Regularization-Based Incremental Learning.

Chi-Chang Lee, Yu-Chen Lin, Hsuan-Tien Lin, Hsin-Min Wang, Yu Tsao

Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels.

Yu-Ting Chou, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama

Proceedings of the 37th International Conference on Machine Learning, 2020

Cold-start Active Learning through Self-supervised Language Modeling.

Michelle Yuan, Hsuan-Tien Lin, Jordan L. Boyd-Graber

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Learning from Label Proportions with Consistency Regularization.

Kuen-Han Tsai, Hsuan-Tien Lin

Proceedings of The 12th Asian Conference on Machine Learning, 2020

2019

Annotation cost-sensitive active learning by tree sampling.

Yu-Lin Tsou, Hsuan-Tien Lin

Mach. Learn., 2019

Dynamic principal projection for cost-sensitive online multi-label classification.

Hong-Min Chu, Kuan-Hao Huang, Hsuan-Tien Lin

Mach. Learn., 2019

Attention-based Deep Tropical Cyclone Rapid Intensification Prediction.

Ching-Yuan Bai, Buo-Fu Chen, Hsuan-Tien Lin

Proceedings of MACLEAN: MAChine Learning for EArth ObservatioN Workshop co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2019), 2019

Advances in Cost-sensitive Multiclass and Multilabel Classification.

Hsuan-Tien Lin

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Deep Learning with a Rethinking Structure for Multi-label Classification.

Yao-Yuan Yang, Yi-An Lin, Hong-Min Chu, Hsuan-Tien Lin

Proceedings of The 11th Asian Conference on Machine Learning, 2019

2018

Automatic Bridge Bidding Using Deep Reinforcement Learning.

Chih-Kuan Yeh, Cheng-Yu Hsieh, Hsuan-Tien Lin

IEEE Trans. Games, 2018

Multi-Label Classification with Feature-Aware Cost-Sensitive Label Embedding.

Hsien-Chun Chiu, Hsuan-Tien Lin

Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2018

Cost-Sensitive Reference Pair Encoding for Multi-Label Learning.

Yao-Yuan Yang, Kuan-Hao Huang, Chih-Wei Chang, Hsuan-Tien Lin

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

REFUEL: Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis.

Yu-Shao Peng, Kai-Fu Tang, Hsuan-Tien Lin, Edward Y. Chang

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Rotation-blended CNNs on a New Open Dataset for Tropical Cyclone Image-to-intensity Regression.

Boyo Chen, Buo-Fu Chen, Hsuan-Tien Lin

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Compatibility Family Learning for Item Recommendation and Generation.

Yong-Siang Shih, Kai-Yueh Chang, Hsuan-Tien Lin, Min Sun

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

A Deep Model With Local Surrogate Loss for General Cost-Sensitive Multi-Label Learning.

Cheng-Yu Hsieh, Yi-An Lin, Hsuan-Tien Lin

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Progressive random k-labelsets for cost-sensitive multi-label classification.

Yuping Wu, Hsuan-Tien Lin

Mach. Learn., 2017

Cost-sensitive label embedding for multi-label classification.

Kuan-Hao Huang, Hsuan-Tien Lin

Mach. Learn., 2017

Soft Methodology for Cost-and-error Sensitive Classification.

Te-Kang Jan, Da-Wei Wang, Chi-Hung Lin, Hsuan-Tien Lin

CoRR, 2017

libact: Pool-based Active Learning in Python.

Yao-Yuan Yang, Shao-Chuan Lee, Yu-An Chung, Tung-En Wu, Si-An Chen, Hsuan-Tien Lin

CoRR, 2017

Cost-Sensitive Encoding for Label Space Dimension Reduction Algorithms on Multi-label Classification.

Kuo-Hsuan Lo, Hsuan-Tien Lin

Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2017

Cyclic Classifier Chain for Cost-Sensitive Multilabel Classification.

Yi-An Lin, Hsuan-Tien Lin

Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

2016

Cost-Sensitive Random Pair Encoding for Multi-Label Classification.

Yao-Yuan Yang, Chih-Wei Chang, Hsuan-Tien Lin

CoRR, 2016

Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation.

Yu-An Chung, Hsuan-Tien Lin

CoRR, 2016

A Simple Unlearning Framework for Online Learning Under Concept Drifts.

Sheng-Chi You, Hsuan-Tien Lin

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016

Linear Upper Confidence Bound Algorithm for Contextual Bandit Problem with Piled Rewards.

Kuan-Hao Huang, Hsuan-Tien Lin

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016

Cost-Aware Pre-Training for Multiclass Cost-Sensitive Deep Learning.

Yu-An Chung, Hsuan-Tien Lin, Shao-Wen Yang

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

A Novel Uncertainty Sampling Algorithm for Cost-Sensitive Multiclass Active Learning.

Kuan-Hao Huang, Hsuan-Tien Lin

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Can Active Learning Experience Be Transferred?

Hong-Min Chu, Hsuan-Tien Lin

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Automatic Bridge Bidding Using Deep Reinforcement Learning.

Chih-Kuan Yeh, Hsuan-Tien Lin

Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA.

Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Active Learning Using Hint Information.

Chun-Liang Li, Chun-Sung Ferng, Hsuan-Tien Lin

Neural Comput., 2015

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

J. Mach. Learn. Res., 2015

A practical divide-and-conquer approach for preference-based learning to rank.

Han-Jay Yang, Hsuan-Tien Lin

Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2015

Active Learning by Learning.

Wei-Ning Hsu, Hsuan-Tien Lin

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Contract Bridge Bidding by Learning.

Chun-Yen Ho, Hsuan-Tien Lin

Proceedings of the Computer Poker and Imperfect Information, 2015

2014

Effective string processing and matching for author disambiguation.

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

J. Mach. Learn. Res., 2014

Improving ranking performance with cost-sensitive ordinal classification via regression.

Yu-Xun Ruan, Hsuan-Tien Lin, Ming-Feng Tsai

Inf. Retr., 2014

Machine Learning Approaches for Interactive Verification.

Yu-Cheng Chou, Hsuan-Tien Lin

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2014

Condensed Filter Tree for Cost-Sensitive Multi-Label Classification.

Chun-Liang Li, Hsuan-Tien Lin

Proceedings of the 31th International Conference on Machine Learning, 2014

Boosting with Online Binary Learners for the Multiclass Bandit Problem.

Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu

Proceedings of the 31th International Conference on Machine Learning, 2014

Reduction from Cost-Sensitive Multiclass Classification to One-versus-One Binary Classification.

Hsuan-Tien Lin

Proceedings of the Sixth Asian Conference on Machine Learning, 2014

Pseudo-reward Algorithms for Contextual Bandits with Linear Payoff Functions.

Ku-Chun Chou, Hsuan-Tien Lin, Chao-Kai Chiang, Chi-Jen Lu

Proceedings of the Sixth Asian Conference on Machine Learning, 2014

2013

Multilabel Classification Using Error-Correcting Codes of Hard or Soft Bits.

Chun-Sung Ferng, Hsuan-Tien Lin

IEEE Trans. Neural Networks Learn. Syst., 2013

Data Selection Techniques for Large-Scale Rank SVM.

Ken-Yi Lin, Te-Kang Jan, Hsuan-Tien Lin

Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2013

Active Learning for Multiclass Cost-Sensitive Classification Using Probabilistic Models.

Po-Lung Chen, Hsuan-Tien Lin

Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2013

Pairwise Regression with Upper Confidence Bound for Contextual Bandit with Multiple Actions.

Ya-Hsuan Chang, Hsuan-Tien Lin

Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2013

Active Sampling of Pairs and Points for Large-scale Linear Bipartite Ranking.

Wei-Yuan Shen, Hsuan-Tien Lin

Proceedings of the Asian Conference on Machine Learning, 2013

2012

Unsupervised Semantic Feature Discovery for Image Object Retrieval and Tag Refinement.

Yin-Hsi Kuo, Wen-Huang Cheng, Hsuan-Tien Lin, Winston H. Hsu

IEEE Trans. Multim., 2012

Multilabel Classification with Principal Label Space Transformation.

Farbound Tai, Hsuan-Tien Lin

Neural Comput., 2012

Reduction from Cost-Sensitive Ordinal Ranking to Weighted Binary Classification.

Hsuan-Tien Lin, Ling Li

Neural Comput., 2012

Novel Models and Ensemble Techniques to Discriminate Favorite Items from Unrated Ones for Personalized Music Recommendation.

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

Proceedings of KDD Cup 2011 competition, San Diego, CA, USA, 2011, 2012

Active Learning with Hinted Support Vector Machine.

Chun-Liang Li, Chun-Sung Ferng, Hsuan-Tien Lin

Proceedings of the 4th Asian Conference on Machine Learning, 2012

A Linear Ensemble of Individual and Blended Models for Music Rating Prediction.

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

Proceedings of KDD Cup 2011 competition, San Diego, CA, USA, 2011, 2012

Feature-aware Label Space Dimension Reduction for Multi-label Classification.

Yao-Nan Chen, Hsuan-Tien Lin

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

A simple methodology for soft cost-sensitive classification.

Te-Kang Jan, Da-Wei Wang, Chi-Hung Lin, Hsuan-Tien Lin

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

An Online Boosting Algorithm with Theoretical Justifications.

Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Multi-label Active Learning with Auxiliary Learner.

Chen-Wei Hung, Hsuan-Tien Lin

Proceedings of the 3rd Asian Conference on Machine Learning, 2011

Multi-label Classification with Error-correcting Codes.

Chun-Sung Ferng, Hsuan-Tien Lin

Proceedings of the 3rd Asian Conference on Machine Learning, 2011

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

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

Cost-Sensitive Classification on Pathogen Species of Bacterial Meningitis by Surface Enhanced Raman Scattering.

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

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2011

2010

One-sided Support Vector Regression for Multiclass Cost-sensitive Classification.

Han-Hsing Tu, Hsuan-Tien Lin

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009

An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naive Bayes.

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

Proceedings of KDD-Cup 2009 competition, Paris, France, June 28, 2009, 2009

2008

From Ordinal Ranking to Binary Classification.

Hsuan-Tien Lin

PhD thesis, 2008

Support Vector Machinery for Infinite Ensemble Learning.

Hsuan-Tien Lin, Ling Li

J. Mach. Learn. Res., 2008

2007

A note on Platt's probabilistic outputs for support vector machines.

Hsuan-Tien Lin, Chih-Jen Lin, Ruby C. Weng

Mach. Learn., 2007

Optimizing 0/1 Loss for Perceptrons by Random Coordinate Descent.

Ling Li, Hsuan-Tien Lin

Proceedings of the International Joint Conference on Neural Networks, 2007

2006

Ordinal Regression by Extended Binary Classification.

Ling Li, Hsuan-Tien Lin

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice.

Hsuan-Tien Lin, Ling Li

Proceedings of the Algorithmic Learning Theory, 17th International Conference, 2006

2005

Improving Generalization by Data Categorization.

Ling Li, Amrit Pratap, Hsuan-Tien Lin, Yaser S. Abu-Mostafa

Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

Infinite Ensemble Learning with Support Vector Machines.

Hsuan-Tien Lin, Ling Li

Proceedings of the Machine Learning: ECML 2005, 2005

2002

A Note on the Decomposition Methods for Support Vector Regression.

Shuo-Peng Liao, Hsuan-Tien Lin, Chih-Jen Lin

Neural Comput., 2002