Chien-Liang Liu
Chien-Liang Liu

Chien-Liang Liu Professor

  • Ph.D., National Chiao Tung University, Taiwan
  • Machine Learning, Deep Learning, Data Mining
+886-3-5712121 ext. 57309 | Email: clliu [at] nycu.edu.tw | Office: MB505 | Lab

代表性著作

著作
Journal paper (2012-2020):
Chien-Liang Liu, Qing-Hong Chen (2020), "Metric-Based Semi-Supervised Regression", IEEE Access, Vol 8, pp. 30001 - 30011
Chien-Liang Liu, Bin Xiao, Wen-Hoar Hsaio, Vincent S. Tseng (2019), "Epileptic Seizure Prediction With Multi-View Convolutional Neural Networks", IEEE Access, Vol 7, pp. 170352-170361
Chien-Liang Liu, Wen-Hoar Hsaio, Yao-Chung Tu (2019), “Time Series Classification With Multivariate Convolutional Neural Network”, IEEE Transactions on Industrial Electronics, Vol 66, No. 6, pp. 4788-4797
Chien-Liang Liu, Po-Yen Hsieh (2019), “Model-based Synthetic Sampling for Imbalanced Data”, To be appeared in IEEE Transactions on Knowledge and Data Engineering
Chien-Liang Liu, Wen-Hoar Hsaio*, Tao-Hsing Chang, Hsuan-Hsun Li (2019), “Clustering data with partial background information”, International Journal of Machine Learning and Cybernetics, Vol 10, pp. 1123-1138
Chien-Liang Liu*, Ying-Chuan Chen (2018), “Background music recommendation based on latent factors and moods”, Knowledge-based Systems, Vol. 159, pp.158-170
Chien-Liang Liu*, Ruey-Shyang Soong, Wei-Chen Lee, De-Hsuan Chen, Shang Hwa Hsu (2018), “A predictive model for acute allograft rejection of liver transplantation”, Expert Systems with Applications, Vol 94, pp. 228-236
Chien-Liang Liu, Wen-Hoar Hsaio, Che-Yuan Lin (2018), “Bayesian Exploratory Clustering with Entropy Chinese Restaurant Process”, Intelligent Data Analysis, Vol. 22, No. 3, pp. 551-568
Chien-Liang Liu, Wen-Hoar Hsaio, Tao-Hsing Chang (2018), ”Locality Sensitive K-means Clustering”, Journal Of Information Science and Engineering Vol. 34, No. 1, pp. 289-305
Wen-Hoar Hsaio, Chien-Liang Liu*, Wei-Liang Wu (2017), “Locality-constrained max-margin sparse coding”, Pattern Recognition, Vol. 65, pp. 285-295
Chien-Liang Liu, Wen-Hoar Hsaio*, Bin Xiao, Chun-Yu Chen, Wei-Liang Wu (2017), “Maximum-Margin Sparse Coding“, Neurocomputing, Vol. 238, pp. 340-350
Chien-Liang Liu, Wen-Hoar Hsaio, Tao-Hsing Chang, Tzai-Min Jou (2017), “Nonparametric Multi-Assignment Clustering”, Intelligent Data Analysis, Vol 21, No.4, pp. 893-911
Chien-Liang Liu*, Xuan-Wei Wu (2016), “Large-scale Recommender System with Compact Latent Factor Model”, Expert Systems With Applications, Vol. 64, pp. 467-475
Chien-Liang Liu*, Xuan-Wei Wu (2016), “Fast Recommendation on Latent Collaborative Relations”, Knowledge-Based Systems, Vol 109, pp. 25-34
Chien-Liang Liu*, Wen-Hoar Hsaio, Chia-Hoang Lee, Tao-Hsing Chang, Tsung-Hsun Kuo (2016), "Semi-supervised Text Classification with Universum Learning", IEEE Transactions on Cybernetics, Vol. 46(2), p.462-473
Chien-Liang Liu*, Wen-Hoar Hsaio, Chia-Hoang Lee, Fu-Sheng Gou (2014), "Semi-Supervised Linear Discriminant Clustering", IEEE Transactions on Cybernetics, 2014, VOL. 44, NO.7 , 989-1000
Chien-Liang Liu*, Wen-Hoar Hsaio, Chia-Hoang Lee, Chun-Hsien Chen (2013), “Clustering Tagged Documents with Labeled and Unlabeled Documents", Information Processing & Management Vol. 49, pp. 596-606
Chien-Liang Liu*, Tao-Hsing Chang, Hsuan-Hsun Li (2013), “Clustering documents with labeled and unlabeled documents using fuzzy semi-Kmeans", Fuzzy Sets and Systems, Vol. 221, pp. 48-64
Chien-Liang Liu*, Wen-Hoar Hsaio , Chia-Hoang Lee and Hsiao-Cheng Chi (2013), “A HMM-based Algorithm for Content Ranking and Coherence Feature Extraction”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol 43, NO. 2, pp. 440–450
Chien-Liang Liu*, Wen-Hoar Hsaio , Chia-Hoang Lee, Gen-Chi Lu and Emery Jou (2012). “Movie Rating and Review Summarization in Mobile Environment”, IEEE Transactions on Systems, Man, and Cybernetics, Part C, Vol. 42, NO. 3, pp. 397-407
Chien-Liang Liu*, Chia-Hoang Lee, and Bo-Yuan Ding (2012). Intelligent Computer Assisted Blog Writing System. Expert Systems With Applications Vol 39, Issue 4, pp. 4496-4504
Conference Paper:
En-Yu Hsu, Chien-Liang Liu, Vincent S. Tseng, "Multivariate Time Series Early Classification with Interpretability Using Deep Learning and Attention Mechanism”, The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2019), pp. 541-553
Yu-Jhen Chen, Chien-Liang Liu, Vincent S. Tseng, Yu-Feng Hu, Shih-Ann Chen (2019), "Large-scale Classification of 12-lead ECG withDeep Learning", To be appeared in IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI 2019)
Hiroki Karasawa, Chien-Liang Liu, Hayato Ohwada, "Deep 3D Convolutional Neural Network Architectures for Alzheimer's Disease Diagnosis”, Asian Conference on Intelligent Information and Database Systems (ACIIDS 2018), pp. 287-296
Huai-Shuo Huang, Chien-Liang Liu, Vincent S. Tseng*, "Multivariate Time Series Early Classification Using Multi-Domain Deep Neural Network”, IEEE International Conference on Data Science and Advanced Analytics (DSAA 2018), pp. 90-98
Yi-Hsun Liu, Chien-Liang Liu, Shin-Mu Tseng*, “Deep Discriminative Features Learning and Sampling for Imbalanced Data Problem”, IEEE International Conference on Data Mining (ICDM 2018), pp. 1146-1151
Chu-En Yu, Chien-Liang Liu*, Hsin-Lung Hsieh, “Hierarchical hypothesis structure for ensemble learning”, International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2017), pp. 1827-1832
Chien-Liang Liu*, Ching-Hsien Lee, “Enhancing Text Classification with the Universum”, International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2016), pp. 1147-1153
Yao-Chung Tu, Ching-Hsien Lee, Wen-Hoar Hsaio, Chien-Liang Liu* (2016), “Data Sampling to Imbalanced Data of Industrial Plant Fault Prediction“, International Symposium on Semiconductor Manufacturing Intelligence (ISMI2016)
Chien-Liang Liu*, Tsung-Hsun Tsai, Chia-Hoang Lee, Online Chinese Restaurant Process (2014), Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, 2014, 591-600 (Full paper, acceptance rate = 14.6%)