Publications
2026
- Peiwen Huang, Chih-Hao Hsu, Tzu-Hung Huang, Shou-De Lin "Role-Sensitive Neurons: A Neuron-Level Gain Control Mechanism for Confidence Steering," in ACL 2026.
- Pei-Fu Guo, Yun-Da Tsai, Chun-Chia Hsu, Kai-Xin Chen, Ya An Tsai, Kai-Wei Chang, Nanyun Peng, Mi-Yen Yeh, Shou-De Lin "LiveCLKTBench: Towards Reliable Evaluation of Cross-Lingual Knowledge Transfer in Multilingual LLMs," in ACL 2026.
- Pei-Fu Guo, Ya An Tsai, Chun-Chia Hsu, Kai-Xin Chen, Yun-Da Tsai, Kai-Wei Chang, Nanyun Peng, Mi-Yen Yeh, Shou-De Lin "Beyond Facts: Benchmarking Distributional Reading Comprehension in Large Language Models," in ACL (Findings) 2026.
- Yu-Che Tsai, Kuan-Yu Chen, Yuan-Chi Li, Yuan-Hao Chen, Ching-Yu Tsai, and Shou-De Lin, "Let LLMs Speak Embedding Languages: Generative Text Embeddings via Iterative Contrastive Refinement," in ICLR 2026.
- Yu-Che Tsai, Hsiang Hsiao, Kuan-Yu Chen, and Shou-De Lin, "Concept-Aware Privacy Mechanisms for Defending Embedding Inversion Attacks," in ICLR 2026.
2025
- Li-Wei Chang, Cheng-Te Li, Chun-Pai Yang, and Shou-de Lin, "Learning on Missing Tabular Data: Attention with Self-Supervision, Not Imputation, Is All You Need," in ACM Trans. Intell. Syst. Technol. 16(3): 73:1-73:24 (2025)
- Yun-Da Tsai, Ting-Yu Yen, Keng-Te Liao, and Shou-De Lin, "Enhance Modality Robustness in Text-Centric Multimodal Alignment with Adversarial Prompting," in AAAI 2025: 27740-27747.
- Guo-Wei Wong, Yi-Ting Huang, Ying-Ren Guo, Ming-Chuan Yang, Shou-De Lin, and Wang-Chien Lee, Meng Chang Chen, "Poster: When Logs Misbehave: Retrieving Known APTs from Noisy Graphs," in CCS 2025: 4776-4778.
- Yun-Da Tsai, Ting-Yu Yen, Pei-Fu Guo, Zhe-Yan Li, and Shou-De Lin, "Text-centric Alignment for Bridging Test-time Unseen Modality," in EMNLP (Findings) 2025: 3826-3845.
- Pei-Fu Guo, Yun-Da Tsai, and Shou-De Lin, "Benchmarking Uncertainty Metrics for LLM Target-Aware Search," in EMNLP (Findings) 2025: 4230-4238.
- Ko-Wei Huang, Yi-Fu Fu, Ching-Yu Tsai, Yu-Chieh Tu, Tzu-ling Cheng, Cheng-Yu Lin, Yi-Ting Yang, Heng-Yi Liu, Keng-Te Liao, Da-Cheng Juan, and Shou-De Lin, "Neuron-Level Differentiation of Memorization and Generalization in Large Language Models," in EMNLP 2025: 16066-16080.
- Yun-Da Tsai, Tzu-Hsien Tsai, and Shou-De Lin, "Differentiable Good Arm Identification," in PAKDD (1) 2025: 253-264.
- Yun-Ang Wu, Yun-Da Tsai, and Shou-De Lin, "LinearAPT: An Adaptive Algorithm for the Fixed-Budget Thresholding Linear Bandit Problem," in PAKDD (1) 2025: 265-277.
2024
- Chao-Min Chang, Cheng-Te Li, and Shou-De Lin, "Unilateral boundary time series forecasting," in Frontiers Big Data 7.
- Yu-Tung Pai, Nien-En Sun, Cheng-Te Li, and Shou-De Lin, "Incremental Data Drifting: Evaluation Metrics, Data Generation, and Approach Comparison," in ACM Trans. Intell. Syst. Technol. 15(4): 71:1-71:26 (2024).
- Yun-Da Tsai, Cayon Liow, Yin Sheng Siang, and Shou-De Lin, "Toward More Generalized Malicious URL Detection Models," in AAAI 2024, pp. 21628-21636.
- Tzu-Hsien Tsai, Yun-Da Tsai, and Shou-De Lin, "lil'HDoC: An Algorithm for Good Arm Identification Under Small Threshold Gap," in PAKDD (5) 2024, pp. 78-89.
- Yun-Da Tsai and Shou-De Lin, "Handling Concept Drift in Non-stationary Bandit Through Predicting Future Rewards," in PAKDD 2024, pp. 161-173.
- Yu-Hsiang Huang, Yu-Che Tsai, Hsiang Hsiao, Hong-Yi Lin, and Shou-De Lin, "Transferable Embedding Inversion Attack: Uncovering Privacy Risks in Text Embeddings without Model Queries," in ACL (1) 2024: 4193-4205.
- Pei-Fu Guo, Ying-Hsuan Chen, Yun-Da Tsai, and Shou-De Lin, "Towards Optimizing with Large Language Model," in KiL@KDD 2024: 1-11.
2023
- PF Guo, YH Chen, YD Tsai, and SD Lin, "Towards optimizing with large language models," in arXiv preprint arXiv:2310.05204.
- Y Jiang, K Liao, S Lin, H Qiao, K Yu, C Yang, and Y Chen, "Self-supervised Multimodal Representation Learning for Product Identification and Retrieval," in International Conference on Neural Information Processing, pp. 579-594.
- F Liawi, YD Tsai, GL Lu, and SD Lin, "PSGText: Stroke-Guided Scene Text Editing with PSP Module," in arXiv preprint arXiv:2310.13366.
- YD Tsai, YC Tsai, BW Huang, CP Yang, and SD Lin, "AutoML-GPT: Large Language Model for AutoML," in arXiv preprint arXiv:2309.01125.
- YT Lee, DY Wu, CC Yang, and SD Lin, "Exposing the Functionalities of Neurons for Gated Recurrent Unit Based Sequence-to-Sequence Model," in arXiv preprint arXiv:2303.15072.
- YD Tsai, TH Tsai, and SD Lin, "Differential Good Arm Identification," in arXiv preprint arXiv:2303.07154.
- CC Li, CT Li, and SD Lin, "Learning Privacy-Preserving Embeddings for Image Data to Be Published," in ACM Transactions on Intelligent Systems and Technology 14(6), pp. 1-26.
- C Liow, CT Li, CP Yang, and SD Lin, "Pseudo Triplet Networks for Classification Tasks with Cross-Source Feature Incompleteness," in Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, pp. 4079-4083.
- K Singh, YC Tsai, CT Li, M Cha, and SD Lin, "GraphFC: Customs Fraud Detection with Label Scarcity," in Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, pp. 4829-4835.
- YC Tseng, ZM Chen, MY Yeh, and SD Lin, "UPGAT: Uncertainty-Aware Pseudo-neighbor Augmented Knowledge Graph Attention Network," in Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 53-65.
2022
- YD Tsai, C Liow, YS Siang, and SD Lin, "Toward more generalized malicious URL detection models," in arXiv.
- BW Huang, KT Liao, CS Kao, and SD Lin, "Environment Diversification with Multi-head Neural Network for Invariant Learning," in Advances in Neural Information Processing Systems 35, pp. 915-927.
- KT Liao, BW Huang, CC Yang, and SD Lin, "Bayesian mixture variational autoencoders for multi-modal learning," in Machine Learning 111(12), pp. 4329-4357.
- TC Shen, CP Yang, IEH Yen, and SD Lin, "Towards l1 Regularization for Deep Neural Networks: Model Sparsity Versus Task Difficulty," in 2022 IEEE 9th International Conference on Data Science and Advanced.
- Y Da Tsai and S De Lin, "Fast online inference for nonlinear contextual bandit based on Generative Adversarial Network," in arXiv preprint arXiv:2202.08867.
- YD Tsai and SD Lin, "Fast Online Inference for Nonlinear Contextual Bandit Based on Generative Adversarial Network," in SSRN 4616034.
- YT Lee, CT Li, and SD Lin, "Conditional Sentence Rephrasing without Parallel Training Corpus," in 2022 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), pp. 1-1.
- CC Yang, CT Li, and SD Lin, "SMITH: A Self-supervised Downstream-Aware Framework for Missing Testing Data Handling," in Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 499-510.
2021
- Chih-Te Lai, Cheng-Te Li, and Shou-De Lin, "Deep Energy Factorization Model for Demographic Prediction," in ACM Transactions on Intelligent Systems and Technology 12(1): 8:1-8:16 (2021).
- S Chen and SD Lin, "EMI for information engineering students: A case study," in Rethinking EMI, pp. 42-60.
- YD Tsai, CK Chen, and SD Lin, "Toward an Effective Black-Box Adversarial Attack on Functional JavaScript Malware against Commercial Anti-Virus," in Proceedings of the 30th ACM International Conference on Information and Knowledge Management, pp. 4165-4172.
2020
- Shu-Kai Zhang, Cheng-Te Li, and Shou-De Lin, "A joint optimization framework for better community detection based on link prediction in social networks," in Knowledge and Information Systems 62(11): 4277-4296 (2020).
- Hong-You Chen, Sz-Han Yu, and Shou-De Lin, "Glyph2Vec: Learning Chinese Out-of-Vocabulary Word Embedding from Glyphs," in ACL 2020, pp. 2865-2871.
- Chin-Hui Chen, Yi-Fu Fu, Hsiao-Hua Cheng, and Shou-De Lin, "Unseen Filler Generalization in Attention-based Natural Language Reasoning Models," in CogMI 2020, pp. 42-51.
- Keng-Te Liao, Zhihong Shen, Chiyuan Huang, Chieh-Han Wu, Po-Chun Chen, Kuansan Wang, and Shou-De Lin, "Explainable and Sparse Representations of Academic Articles for Knowledge Exploration," in COLING 2020, pp. 6207-6216.
- Yu-Sheng Chou, Chien-Yao Wang, Shou-De Lin, and Hong-Yuan Mark Liao, "How Incompletely Segmented Information Affects Multi-Object Tracking and Segmentation (MOTS)," in ICIP 2020, pp. 2086-2090.
- Keng-Te Liao, Cheng-Syuan Lee, Zhong-Yu Huang, and Shou-De Lin, "Explaining Word Embeddings via Disentangled Representation," in AACL/IJCNLP 2020, pp. 720-725.
2019
- Jia-Yun Jiang, Cheng-Te Li, and Shou-De Lin, "Towards a more reliable privacy-preserving recommender system," in Information Sciences 482: 248-265 (2019).
- Yi-An Lai, Chin-Chi Hsu, Wen-Hao Chen, Mi-Yen Yeh, and Shou-De Lin, "DeepRank: improving unsupervised node ranking via link discovery," in Data Mining and Knowledge Discovery.
- Wen-Hao Chen, Chin-Chi Hsu, Yi-An Lai, Vincent Liu, Mi-Yen Yeh, and Shou-De Lin, "Attribute-Aware Recommender System Based on Collaborative Filtering: Survey and Classification," in Frontiers Big Data 2: 49.
- Jun-Kun Wang, Chi-Jen Lu, and Shou-De Lin, "Online Linear Optimization with Sparsity Constraints," in ALT 2019.
- Fan-Yun Sun, Yen-Yu Chang, Yueh-Hua Wu, and Shou-De Lin, "A Regulation Enforcement Solution for Multi-agent Reinforcement Learning," in AAMAS 2019.
- Ming-Han Feng, Chin-Chi Hsu, Cheng-Te Li, Mi-Yen Yeh, and Shou-De Lin, "MARINE: Multi-relational Network Embeddings with Relational Proximity and Node Attributes," in WWW 2019.
- Szu-Wei Fu, Chien-Feng Liao, Yu Tsao, and Shou-De Lin, "MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement," in ICML 2019, pp. 2031-2041.
- Hong-You Chen, Chin-Hua Hu, Leila Wehbe, and Shou-De Lin, "Self-Discriminative Learning for Unsupervised Document Embedding," in NAACL-HLT 2019, pp. 2465-2474.
- Yu-Sheng Chou, Chien-Yao Wang, Ming-Chiao Chen, Shou-De Lin, and Hong-Yuan Mark Liao, "Dynamic Gallery for Real-Time Multi-Target Multi-Camera Tracking," in AVSS 2019, pp. 1-8.
- Sakura Yamaki, Shou-De Lin, and Wataru Kameyama, "Detection of Anomaly State Caused by Unexpected Accident using Data of Smart Card for Public Transportation," in IEEE BigData 2019, pp. 1693-1698.
- Yue Liu, Helena Lee, Palakorn Achananuparp, Ee-Peng Lim, Tzu-Ling Cheng, and Shou-De Lin, "Characterizing and Predicting Repeat Food Consumption Behavior for Just-in-Time Interventions," in PDH 2019, pp. 11-20.
- Liang-Hsin Shen, Pei-Lun Tai, Chao-Chung Wu, and Shou-De Lin, "Controlling Sequence-to-Sequence Models - A Demonstration on Neural-based Acrostic Generator," in EMNLP/IJCNLP 2019, pp. 43-48.
- Chih-Te Lai, Yi-Te Hong, Hong-You Chen, Chi-Jen Lu, and Shou-De Lin, "Multiple Text Style Transfer by using Word-level Conditional Generative Adversarial Network with Two-Phase Training," in EMNLP/IJCNLP 2019, pp. 3577-3582.
- Szu-Wei Fu, Chien-Feng Liao, Yu Tsao, and Shou-De Lin, "MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement," in ICML 2019, pp. 2031-2041.
- Hong-You Chen, Chin-Hua Hu, Leila Wehbe, and Shou-De Lin, "Self-Discriminative Learning for Unsupervised Document Embedding," in NAACL-HLT 2019, pp. 2465-2474.
- Chao-Chung Wu, Ruihua Song, Tetsuya Sakai, Wen-Feng Cheng, Xing Xie, and Shou-De Lin, "Evaluating Image-Inspired Poetry Generation," in NLPCC 2019, pp. 539-551.
- Kung-Hsiang Huang, Yi-Fu Fu, Yi-Ting Lee, Tzong-Hann Lee, Yao-Chun Chan, Yi-Hui Lee, and Shou-De Lin, "A-HA: a hybrid approach for hotel recommendation," in RecSys Challenge 2019, 4:1-4:5.
- Ming-Han Feng, Chin-Chi Hsu, Cheng-Te Li, Mi-Yen Yeh, and Shou-De Lin, "MARINE: Multi-relational Network Embeddings with Relational Proximity and Node Attributes," in WWW 2019, pp. 470-479.
2018
- Chin-Chi Hsu, Mi-Yen Yeh, and Shou-De Lin, "A General Framework for Implicit and Explicit Social Recommendation," in IEEE Transactions on Knowledge and Data Engineering.
- Cheng-Te Li and Shou-De Lin, "Social Flocks: Simulating Crowds to Discover the Connection Between Spatial-Temporal Movements of People and Social Structure," in IEEE Transactions on Computational Social Systems 5(1): 33-45 (2018).
- Ian En-Hsu Yen, Wei-Cheng Lee, Kai Zhong, Sung-En Chang, Pradeep Ravikumar, and Shou-De Lin, "MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization," in NIPS 2018.
- Hong-You Chen, Cheng-Syuan Lee, Keng-Te Liao, and Shou-De Lin, "Word Relation Autoencoder for Unseen Hypernym Extraction Using Word Embeddings," in EMNLP 2018.
- Yueh-Hua Wu and Shou-De Lin, "A Low-Cost Ethics Shaping Approach for Designing Reinforcement Learning Agents," in AAAI 2018.
- FY Sun, YY Chang, YH Wu, and SD Lin, "Designing Non-greedy Reinforcement Learning Agents with Diminishing Reward Shaping," in AIES 2018.
- Yian Chen, Xing Xie, Shou-De Lin, and Arden Chiu, "WSDM Cup 2018: Music Recommendation and Churn Prediction," in WSDM Cup 2018.
- Yu-Sheng Chou, Pai-Heng Hsiao, Shou-De Lin, and Hong-Yuan Mark Liao, "How Sampling Rate Affects Cross-Domain Transfer Learning for Video Description," in ICASSP 2018.
- Fang-Yi Chang, Chun Chen, and Shou-De Lin, "An Empirical Study of Ladder Network and Multitask Learning on Energy Disaggregation in Taiwan," in TAAI 2018.
- Yueh-Hua Wu, Fan-Yun Sun, Yen-Yu Chang, and Shou-De Lin, "ANS: Adaptive Network Scaling for Deep Rectifier Reinforcement Learning Models," in arXiv preprint.
- Wen-Hao Chen, Chin-Chi Hsu, Yi-An Lai, Vincent Liu, Mi-Yen Yeh, and Shou-De Lin, "Attribute-aware Collaborative Filtering: Survey and Classification," in arXiv preprint.
2017
- Chin-Chi Hsu, Yi-An Lai, Wen-Hao Chen, Ming-Han Feng, and Shou-De Lin, "Unsupervised Ranking using Graph Structures and Node Attributes," in WSDM 2017.
- Ian En-Hsu Yen, Wei-Cheng Lee, Sung-En Chang, Arun Sai Suggala, Shou-De Lin, and Pradeep Ravikumar, "Latent Feature Lasso," in ICML 2017.
- Hao-En Sung, Cheng-Kuan Chen, Han Xiao, and Shou-De Lin, "A Classification Model for Diverse and Noisy Labelers," in PAKDD 2017.
- Jun-Kun Wang, Chi-Jen Lu, and Shou-De Lin, "Fast Algorithm for Logistic Bandit," in AAAI 2017.
- Yi-An Lai, Chin-Chi Hsu, Wen Hao Chen, Mi-Yen Yeh, and Shou-De Lin, "Preserving Proximity and Global Ranking for Network Embedding," in NIPS 2017.
- Hao-Ying Liang, Yun-Tung Shieh, Addicam Sanjay, Shao-Wen Yang, and Shou-De Lin, "Ensemble-Based Location Tracking Using Passive RFID," in DSAA 2017.
- Eric L. Lee, Tsung-Ting Kuo, and Shou-De Lin, "A Collaborative Filtering-Based Two Stage Model with Item Dependency for Course Recommendation," in DSAA 2017.
- Yi-An Lai, Chin-Chi Hsu, Wen-Hao Chen, Mi-Yen Yeh, and Shou-De Lin, "PRUNE: Preserving Proximity and Global Ranking for Network Embedding," in NIPS 2017.
2016
- Chi-Ruei Li, Addicam Sanjay, Shao-Wen Yang, and Shou-De Lin, "Transfer learning for sequential recommendation model," in TAAI 2016.
- Yu-Yang Huang, Rui Yan, Tsung-Ting Kuo, and Shou-De Lin, "A Study on Dispersion Measures for Core Vocabulary Compilation," in IJCLCLP 21(1), 2016.
- Ming-Han Feng, Kuan-Hou Chan, Huan-Yuan Chen, Ming-Feng Tsai, Mi-Yen Yeh, and Shou-De Lin, "An Efficient Solution to Reinforce Paper Ranking using Author/Venue/Citation Information - The Winner's Solution for WSDM Cup 2016," in WSDM Cup Workshop, WSDM 2016.
- Yu-Yang Huang and Shou-De Lin, "Transferring User Interests Across Websites with Unstructured Text for Cold-Start Recommendation," in EMNLP 2016.
- Chia-Hsin Ting, Hung-Yi Lo, and Shou-De Lin, "Transfer-Learning Based Model for Reciprocal Recommendation," in PAKDD 2016.
- Jun-Kun Wang and Shou-De Lin, "Efficient Sampling-based ADMM for Distributed Data," in DSAA 2016.
- Jun-Kun Wang and Shou-De Lin, "Parallel Least-Squares Policy Iteration," in DSAA 2016.
2015
- Cheng-Te Li, Man-Kwan Shan, and Shou-De Lin, "On Team Formation with Expertise Query in Collaborative Social Networks," in Knowledge and Information Systems (KAIS), 2015.
- Guang-He Lee and Shou-De Lin, "LambdaMF: Learning Nonsmooth Ranking Functions in Matrix Factorization Using Lambda," in IEEE ICDM 2015.
- Hsun-Ping Hsieh, Shou-De Lin, and Yu Zheng, "Inferring Air Quality for Station Location Recommendation Based on Urban Big Data," in ACM SIGKDD 2015.
- Su-Chene Lin, Shou-De Lin, and Ming-Syan Chen, "A Learning-based Framework to handle Multi-round Multi-party influence maximization on social networks," in ACM SIGKDD 2015.
- Hsun-Ping Hsieh, Cheng-Te Li, and Shou-De Lin, "Estimating Potential Customers Anywhere and Anytime on Location-based Social Networks," in ECML/PKDD 2015.
- Ian E.H. Yen, Shan-Wei Lin, and Shou-De Lin, "A Dual-Augmented Block Minimization Framework for Learning with Limited Memory," in Advances in Neural Information Processing Systems (NIPS), 2015.
- Yen-Kai Wang, Wei-Ming Chen, Cheng-Te Li, and Shou-De Lin, "Identifying Smallest Unique Subgraphs in a Heterogeneous Social Network," in IEEE International Conference on Big Data 2015.
- Chung-Yi Li, Wei-Lun Su, Todd G. McKenzie, Fu-Chun Hsu, Shou-De Lin, Phillip B. Gibbons, and Jane Yung-jen Hsu, "Recommending Missing Sensor Values," in IEEE International Conference on Big Data 2015.
- Chin-Chi Hsu, Perng-Hwa Kung, Mi-Yen Yeh, Shou-De Lin, and Phillip B. Gibbons, "Bandwidth-Efficient Distributed k-Nearest-Neighbor Search with Dynamic Time Warping," in IEEE International Conference on Big Data 2015.
- Han Xiao, Shou-De Lin, Mi-Yen Yeh, Phillip Gibbons, and Claudia Eckert, "Learning Better while Sending Less: Communication-Efficient Online Semi-Supervised Learning in Client-Server Settings," in DSAA 2015.
2014
- Jing-Kai Lou, Fu-Min Wang, Chin-Hua Tsai, San-Chuan Hung, Perng-Hwa Kung, Shou-De Lin, Kuan-Ta Chen, and Chin-Laung Lei, "A Social Diffusion Model with an Application on Election Simulation," in The Scientific World Journal, Volume 2014 (2014).
- Hsun-Ping Hsieh, Cheng-Te Li, and Shou-De Lin, "Measuring and Recommending Time-Sensitive Routes from Location-based Data," in ACM Transactions on Intelligent Systems and Technology (TIST), Volume 5, Issue 3, 2014.
- Cheng-Te Li, Hsun-Ping Hsieh, Tsung-Ting Kuo, and Shou-De Lin, "Opinion Diffusion and Analysis on Social Networks," in Encyclopedia of Social Network Analysis and Mining, 2014.
- 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, and Chih-Jen Lin, "Effective String Processing and Matching for Author Disambiguation," in Journal of Machine Learning Research.
- En-Hsu Yen, Ting-Wei Lin, Shou-De Lin, Pradeep Ravikumar, and Inderjit Dhillon, "Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space," in NIPS 2014.
- Jun-Kun Wang and Shou-de Lin, "Robust Inverse Covariance Estimation under Noisy Measurements," in the International Conference on Machine Learning (ICML) 2014.
- Yu-Yang Huang, Rui Yan, Tsung-Ting Kuo and Shou-De Lin, "Enriching Cold Start Personalized Language Model Using Social Network Information", ACL 2014.
- Chia-Jen Lin, Tsung-Ting Kuo, and Shou-De Lin, "A Content-based Matrix Factorization Model for Recipe Recommendation", PAKDD 2014.
- Chung-Yi Li and Shou-De Lin, "Matching Users and Items Across Domains to Improve the Recommendation Quality," in ACM SIGKDD 2014.
- Kuan-Wen Chen, Hsin-Mu Tsai, Chih-Hung Hsieh, Shou-De Lin, Chieh-Chih Wang, Shao-Wen Yang, Shao-Yi Chien, Chia-Han Lee, Yu-Chi Su, Chun-Ting Chou, Yuh-Jye Lee, Hsing-Kuo Pao, Ruey-Shan Guo, Chung-Jen Chen, Ming-Hsuan Yang, Bing-Yu Chen, and Yi-Ping Hung, "Connected Vehicle Safety Science, System, and Framework", IEEE World Forum on Internet of Things (WF-IoT), 2014.
- Wei-Shih Lin, Tsung-Ting Kuo, Yu-Yang Huang, Wan-Chen Lu, and Shou-De Lin, "A Transfer-Learning Approach to Exploit Noisy Information for Classification and Its Application on Sentiment Detection," in TAAI 2014.
- Yu-Yang Huang, Yu-An Yen, Ting-Wei Ku, Shou-De Lin, Wen-Tai Hsieh, and Tsun Ku, "A Weight-Sharing Gaussian Process Model Using Web-Based Information for Audience Rating Prediction," in TAAI 2014.
- How Jing and Shou-De Lin, "Neural Conditional Energy Models for Multi-Label Classification," in ICDM 2014.
- Hsun-Ping Hsieh, Cheng-Te Li, and Shou-De Lin, "TripRouter: A Time-Sensitive Route Recommender System", in ICDM 2014.
- How Jing, An-Chun Liang, Shou-De Lin, and Yu Tsao, "A Transfer Probabilistic Collective Factorization Model to Handle Sparse Data in Collaborative Filtering," in ICDM 2014.
- Cho-Yi Hsiao, Hung-Yi Lo, Tu-Chun Yin, and Shou-De Lin, "Optimizing Specificity under Perfect Sensitivity for Medical Data Classification," in International Conference on Data Science and Advanced Analytics, 2014 .
- Jung-Jung Yeh, Tsung-Ting Kuo, William Chen, and Shou-De Lin, "Minimizing Expected Loss for Risk-Avoiding Reinforcement Learning," in International Conference on Data Science and Advanced Analytics, 2014.
- Chin-Hua Tsai, Jing-Kai Lou, Wan-Chen Lu, and Shou-De Lin, "Exploiting Rank-Learning Models to Predict the Diffusion of Preferences on Social Networks," in ASONAM 2014.
- Eric L. Lee, Jing-Kai Lou, Wei-Ming Chen, Yen-Chi Chen, Shou-De Lin, Yen-Sheng Chiang, and Kuan-Ta Chen, "A Fairness-Aware Loan Recommender Syetem for Microfinance Services," in SocialCom, August 2014.
- Shun-Hsing Ou, Yu-Chen Lu, Jui-Pin Wang, Shao-Yi Chien, Shou-De Lin, Mi-Yen Yeh, Chia-Han Lee, Phillip Gibbons, V. Srinivasa Somayazulu, and Yen-Kuang Chen, "Communication-Efficient Multi-view Keyframe Extraction in Distributed Video Sensors," in IEEE VCIP, December 2014.
2013
- Hung-Yi Lo, Shou-De Lin, and Hsin-Min Wang, "Generalized k-Labelsets Ensemble for Multi-Label and Cost-Sensitive Classification," in IEEE Transactions on Knowledge and Data Engineering.
- Yi-Chen Lo, Hung-Che Lai, Cheng-Te Li, and Shou-De Lin, "Mining and Generating Large-Scaled Social Networks via MapReduce," in Social Network Analysis and Mining (SNAM), 2013.
- Yi-Chen Lo, Jhao-Yin Li, Mi-Yen Yeh, Shou-De Lin, and Jian Pei, "What Distinguish One from Its Peers in Social Networks?," in Data Mining and Knowledge Discovery, Volume 27, Issue 3, pp. 396-420, November 2013.
- Yu-Chih Chen, Yu-Shi Lin, Yu-Chun Shen, and Shou-De Lin, "A Modified Random Walk Framework for Handling Negative Ratings and Generating Explanations," in ACM Transactions on Intelligent Systems and Technology, 2013, Vol. 4, No. 1.
- Wan-Chen Lin, Tsung-Ting Kuo, Tung-Jia Chang, Chueh-An Yen, Chao-Ju Chen, and Shou-De Lin, "Exploiting Machine Learning Models for Chinese Legal Documents Labeling, Case Classification, and Sentencing Prediction," in IJCLCLP.
- Jung-Wei Chou, Min-Huang Chu, Yi-Lin Tsai, Yun Jin, Chen-Mou Cheng, and Shou-De Lin, "An unsupervised learning model to perform side channel attack," in Advances in Knowledge Discovery and Data Mining, 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" in KDD Cup 2013 Workshop. (track 1, 1st place)
- Jung-Wei Chou, Yi-Lin Tsai, Min-Huang Chu, Shou-De Lin, Yun Jin, and Chen-Mou Cheng, "Exploiting Machine Learning Techniques to Perform Side Channel Attack," in PAKDD 2013.
- Cheng-Lun Yang, Perng-Hwa Kungy, Cheng-Te Li, Chun-An Chen, Shou-De Lin." Sampling Heterogeneous Networks".ICDM 2013.
- Jui-Pin Wang, Yu-Chen Lu, Mi-Yen Yeh, Shou-De Lin, and Phillip B. Gibbons, "Communication-Efficient Distributed Multiple Reference Pattern Matching for M2M Systems," in IEEE ICDM 2013.
- Ian E.H. Yen, Chun-Fu Chang, Ting-Wei Lin, Shan-Wei Lin, Shou-De Lin, "Indexed Block Coordinate Descent for Large-Scale Linear Classification with Limited Memory", ACM SIGKDD 2013.
- Tsung-Ting Kuo, Rui Yan, Yu-Yang Huang, Perng-Hwa Kung, Shou-De Lin, "Unsupervised Link Prediction Using Aggregative Statistics on Heterogeneous Social Networks", ACM SIGKDD 2013.
- Cheng-Lun Yang, Perng-Hwa Kung, Chun-An Chen, Shou-De Lin, "Semantically Sampling in Heterogeneous Social Networks", WWW 2013.
- Yu-Chun Shen, Tsung-Ting Kuo, I-Ning Yeh, Tzu-Ting Chen, Shou-De Lin, "Exploiting Temporal Information in a Two-stage Classification Framework for Content-based Depression Detection", PAKDD 2013.
- Jing-Kai Lou, Fu-Min Wang, Chin-Hua Tsai, San-Chuan Hung, Perng-Hwa Kung, and Shou-De Lin, "Modeling the Diffusion of Preferences On Social Networks", SIAM International Conference on Data Mining 2013.
- Rui Yan, Han Jiang, Mirella Lapata, Shou-De Lin, Xueqiang Lv, and Xiaoming Li, "i, Poet: Automatic Chinese Poetry Composition through a Generative Summarization Framework under Constrained Optimization," in IJCAI 2013.
- Rui Yan, Han Jiang, Mirella Lapata, Shou-De Lin, Xueqiang Lv, and Xiaoming Li, "Semantic v.s. Positions: Utilizing Balanced Proximity in Language Model Smoothing for Information Retrieval," in IJCNLP 2013.
2012
- Cheng-Te Li, Tsung-Ting Kuo, Chien-Tung Ho, San-Chuan Hong, Wei-Shih Lin, and Shou-De Lin, "Modeling and Evaluating Information Propagation in a Microblogging Social Network," in Social Network Analysis and Mining (SNAM), 2012.
- En-Hsu Yen, Nanyun Peng, Po-Wei Wang, Shou-de Lin, "On Convergence Rate of Concave-Convex Procedure," in NIPS Optimization Workshop 2012.
- Tsung-Hsien Chiang, Hung-Yi Lo, and Shou-de Lin, "A Ranking-based KNN Approach for Multi-Label Classification," in Asia Conference on Machine Learning (ACML 2012).
- Jung-Wei Chou, Shou-De Lin and Chen-Mou Cheng, "On the Effectiveness of using State-of-the-art Machine Learning Techniques to Launch Cryptographic Distinguishing Attacks," in 5th ACM Workshop on Artificial Intelligence and Security (AISEC 2012).
- Min-Huang Chu, Wen-Yu Chen, and Shou-De Lin, "A Learning-based Framework to Utilize E-HowNet Ontology and Wikipedia Sources to Generate Multiple-Choice Factual Questions," in TAAI 2012.
- Wan-Chen Lin, Tsung-Ting Kuo, Tung-Jia Chang, Chueh-An Yen, Chao-Ju Chen and Shou-de Lin, "Exploiting Machine Learning Models for Chinese Legal Documents Labeling, Case Classification, and Sentencing Prediction," in ROCLING 2012.
- Po-Tzu Chang, Yen-Chieh Huang, Cheng-Lun Yang, Shou-De Lin, and Pu-Jen Cheng, "Learning-Based Time-Sensitive Re-Ranking for Web Search," in SIGIR 2012.
- Hun-Hsuan Chen, Yan-Bin Ciou, and Shou-De Lin, "Information Propagation Game: a Tool to Acquire Human Playing Data for Multi-Player Influence Maximization on Social Networks," in KDD 2012.
- Hung-Che Lai, Cheng-Te Li, Yi-Chen Lo, and Shou-De Lin, "Exploiting and Evaluating MapReduce for Large-Scale Graph Mining," in ASONAM 2012.
- Hsun-Ping Hsieh, Cheng-Te Li, and Shou-De Lin, "Exploiting Large-Scale Check-in Data to Recommend Time-Sensitive Routes," in ACM SIGKDD International Workshop on Urban Computing (UrbComp 2012).
- Hsun-Ping Hsieh, Cheng-Te Li, and Shou-De Lin, "TripRec: Recommending Trip Routes from Large Scale Check-in Data," in WWW 2012.
- Hsun-Ping Hsieh, Cheng-Te Li, and Shou-De Lin, "Frequent Temporal Social Behavior Search in Information Networks," in WWW 2012.
- Cheng-Te Li, Man-Kwan Shan, and Shou-De Lin, "Dynamic Selection of Activation Targets to Boost the Influence Spread in Social Networks," in WWW 2012.
- Cheng-Te Li, Hsun-Ping Hsieh, Shou-De Lin, and Man-Kwan Shan, "Finding Influential Seed Successors in Social Networks," in WWW 2012.
- Cheng-Te Li, Man-Kwan Shan, and Shou-De Lin, "Regional Subgraph Discovery in Social Networks," in WWW 2012.
- Cheng-Te Li, Shou-De Lin, and Man-Kwan Shan, "Influence Propagation and Maximization for Heterogeneous Social Networks," in WWW 2012.
- Cheng-Te Li, Hsun-Ping Hsieh, and Shou-De Lin, "CrowDiffuse: Information Diffusion over Crowds with Social Network," in ACM SIGGRAPH 2012.
- Cheng-Te Li and Shou-De Lin, "EvaPlanner: An Evacuation Planner with Social-based Flocking Kinetics," in ACM KDD 2012.
- Cheng-Te Li and Shou-De Lin, "Centrality Analysis, Role-based Clustering, and Egocentric Abstraction for Heterogeneous Social Networks," in IEEE SocialCom 2012.
- Kuan-Wei Wu, Chun-Sung Ferng, Chia-Hua Ho, An-Chun Liang, Chun-Heng Huang, Wei-Yuan Shen, Jyun-Yu Jiang, Ming-Hao Yang, Ting-Wei Lin, Ching-Pei Lee, Perng-Hwa Kung, Chin-En Wang, Ting-Wei Ku, Chun-Yen Ho, Yi-Shu Tai, I-Kuei Chen, Wei-Lun Huang, Che-Ping Chou, Tse-Ju Lin, Han-Jay Yang, Yen-Kai Wang, Cheng-Te Li, Shou-De Lin, and Hsuan-Tien Lin, "A Two-Stage Ensemble of Diverse Models for Advertisement Ranking in KDD Cup 2012," in ACM KDD Cup 2012 Workshop, 2012.
- Yi-Chen Lo, Cheng-Te Li, and Shou-De Lin, "Parallelizing Preferential Attachment Models for Generating Large-Scale Social Networks that Cannot Fit into Memory," in IEEE SocialCom 2012.
- Wan-Yu Lin, Nanyun Peng, Chun-Chao Yen, and Shou-De Lin, "Online Plagiarism Detection Through Exploiting Lexical, Syntactic, and Semantic Information," in ACL 2012.
- Tsung-Ting Kuo, San-Chuan Hung, Wei-Shih Lin, Nanyun Peng, Shou-De Lin, and Wei-Fen Lin, "Exploiting Latent Information to Predict Diffusions of Novel Topics on Social Networks," in ACL 2012.
- Hung-Yi Lo, Shou-De Lin, and Hsin-Min Wang, "Generalized k-Labelset Ensemble for Multi-label Classification," in IEEE Int. Conf. Acoustics, Speech, and Signal Processing (ICASSP 2012), Kyoto, Japan, March 2012.
- Liang-Chieh Chen, Tsung-Ting Kuo, Wei-Chi Lai, Shou-De Lin, Chi-Hung Tsai, "Prediction-Based Outlier Detection with Explanations.", FFDM 2012.
- Wan-Yu Lin, Nanyun Peng, Chun-Chao Yen, and Shou-De Lin, "Online Plagiarized Detection Through Exploiting Lexical, Syntax, and Semantic Information," in ACL (System Demonstrations) 2012.
2011
- Yi-Kuang Ko, Jing-Kai Lou, Cheng-Te Li, Shou-De Lin, and Shyh-Kang Jeng, "A Social Network Evolution Model Based on Seniority," in Social Network Analysis and Mining Journal.
- Hung-Yi Lo, Ju-Chiang Wang, Hsin-Min Wang, and Shou-De Lin, "Cost-sensitive Multi-label Learning for Audio Tag Annotation and Retrieval," in IEEE Transactions on Multimedia, 18(3), pp. 518-529, June 2011.
- Tsung-Ting Kuo and Shou-De Lin, "Learning-Based Concept-Hierarchy Refinement through Exploiting Topology, Content and Social Information," in Information Sciences, 2011.
- Hsun-Ping Hsieh, Cheng-Te Li, and Shou-De Lin, "BeTracker: A System for Finding Behavioral Patterns from Contextual Sensor and Social Data," in IEEE International Conference on Data Mining (ICDM 2011), Demo Paper.
- Chien-Tung Ho, Cheng-Te Li, and Shou-De Lin, "Modeling and Visualizing Information Propagation in a Micro-blogging Platform," in ASONAM 2011.
- Cheng-Te Li, Chien-Yuan Wang, Chien-Lin Tseng, and Shou-De Lin, "MemeTube: A Sentiment-based Audiovisual System for Analyzing and Displaying Microblog Messages," in ACL 2011 Demo Paper.
- Cheng-Te Li, Shou-De Lin, and Man-Kwan Shan, "Finding Influential Mediators in Social Networks," in WWW 2011 Poster Paper.
- Cheng-Te Li, Shou-De Lin, and Man-Kwan Shan, "Exploiting Endorsement Information and Social Influence for Item Recommendation," in ACM SIGIR 2011 Poster Paper.
- Cheng-Te Li and Shou-De Lin, "Social Flocks: A Crowd Simulation Framework for Social Network Generation, Community Detection, and Collective Behavior Modeling," in ACM KDD 2011 Demo Paper.
- Cheng-Te Li, Man-Kwan Shan, and Shou-De Lin, "Context-based People Search in Labeled Social Networks," in ACM CIKM 2011.
- Hsiang-Fu Yu, Hung-Yi Lo, Hsun-Ping Hsieh, Jing-Kai Lou, Todd G. McKenzie, Jung-Wei Chou, Po-Han Chung, Chia-Hua Ho, Chun-Fu Chang, Yin-Hsuan Wei, Jui-Yu Weng, En-Syu Yan, Che-Wei Chang, Tsung-Ting Kuo, Yi-Chen Lo, Po Tzu Chang, Chieh Po, Chien-Yuan Wang, Yi-Hung Huang, Chen-Wei Hung, Yu-Xun Ruan, Yu-Shi Lin, Shou-de Lin, Hsuan-Tien Lin, Chih-Jen Lin "Feature engineering and classifier ensemble for KDD Cup 2010," in Journal of Machine Learning Research, Workshop and Conference Proceedings, 2011.
- Hung-Yi Lo, Ju-Chiang Wang, Hsin-Min Wang, and Shou-De Lin, "Cost-sensitive Multi-label Learning for Audio Tag Annotation and Retrieval," in ICASSP 2011.
- Hung-Yi Lo, Shou-De Lin, and Hsin-Min Wang, "Audio Tag Annotation and Retrieval Using Tag Count Information," in MMM 2011, pp. 339-349.
- Jui-Yu Weng, Cheng-Lun Yang, Bo-Nian Chen, Yen-Kai Wang, and Shou-De Lin, "IMASS: An Intelligent Microblog Analysis and Summarization System," in ACL 2011 System Demonstrations.
- Tsung-Ting Kuo, San-Chuan Hung, Wei-Shih Lin, Shou-De Lin, Ting-Chun Peng, and Chia-Chun Shih "Assessing the Quality of Diffusion Models using Real-World Social Network Data," in TAAI 2011 (accepted as short paper).
- Rumi Ghosh, Tsung-Ting Kuo, Chun-Nan Hsu, Shou-De Lin, and Kristina Lerman, "Time-aware Ranking in Dynamic Citation Networks," in Proceedings of ICDM Workshop on Mining Communities and People Recommenders (COMMPER2011), Vancouver, Canada, 2011.
- 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, and Shou-De Lin, "A Linear Ensemble of Individual and Blended Models for Music Rating Prediction," in Proceedings of KDD-Cup 2011 Competition.
- 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, and Shou-De Lin, "Novel Models and Ensemble Techniques to Discriminate Favorite Items from Unrated Ones for Personalized Music Recommendation," in Proceedings of KDD-Cup 2011 Competition.
- Cheng-Te Li, Hsun-Ping Hsieh, and Shou-De Lin, "Large-scale Heterogeneous Network Data Analysis," in Proceedings of the 19th ACM International Conference on Multimedia.
- Cheng-Te Li, Hsun-Ping Hsieh, and Shou-De Lin, "PhotoFeel: feeling your photo collection with graph-based audiovisual flocking," in Proceedings of the 19th ACM International Conference on Multimedia.
2010
- Cheng-Te Li and Shou-De Lin, "Communication Structure Discovery via Information Asymmetry in an Organizational Social Network," in IEEE/WIC/ACM International Conference on Web Intelligence (WI 2010), 2010.
- Cheng-Te Li, Hung-Che Lai, Chien-Tung Ho, Chien-Lin Tseng, and Shou-De Lin, "Pusic: musicalize microblog messages for summarization and exploration," in WWW 2010 Poster Paper.
- Cheng-Te Li, Hsun-Ping Hsieh, Tsung-Ting Kuo, and Shou-De Lin, "SocioCrowd: A Social-Network-Based Framework for Crowd Simulation," in SIGGRAPH 2010 Poster Paper.
- Tsung-Hsien Chiang, Hung-Yi Lo, and Shou-De Lin, "A Ranking-based KNN Approach for Multilabel Classification," in Workshop on Machine Learning Research in Taiwan: Challenges and Directions (MLRT@TAAI 2010).
- Jing-Kai Lou, Shou-De Lin, Kuan-Ta Chen, and Chin-Laung Lei, "What Can the Temporal Social Behavior Tell Us? An Estimation of Vertex-Betweenness Using Dynamic Social Informations," in ASONAM 2010.
- Tsung-Ting Kuo, Jung-Jung Yeh, Chia-Jen Lin, and Shou-De Lin, "Designing, Analyzing and Exploiting Stake-based Social Networks," in ASONAM 2010 Poster Paper, Denmark.
- Tsung-Ting Kuo, Jung-Jung Yeh, Chia-Jen Lin, and Shou-De Lin, "StakeNet: Devise, Study and Utilize Social Networks using Stakeholder Information," in Conference on Technologies and Applications of Artificial Intelligence, 2010.
- Anta Huang, Tsung-Ting Kuo, Ying-Chun Lai, and Shou-De Lin, "Identifying Correction Rules for Auto Editing," in Proceedings of the 22nd Conference on Computational Linguistics and Speech Processing, 2010.
- Chun-Chao Yen, Liang-Chieh Chen, and Shou-De Lin, "Unsupervised Feature Selection: Minimize Information Redundancy of Features," in Technologies and Applications of Artificial Intelligence, 2010.
Before 2010
- Anta Huang, Tsung-Ting Kuo, Ying-Chun Lai, and Shou-De Lin, "Discovering Correction Rules for Auto Editing," in IJCLCLP, 2010.
- Shou-De Lin and Hans Chalupsky, "Discovering and Explaining Abnormal Nodes in Semantic Graphs," in IEEE Transactions on Knowledge and Data Engineering, Vol. 20, No. 8, 2008.
- Hung-Yi Lo, Chun-Min Chang, Tsung-Hsien Chiang, Cho-Yi Hsiao, Anta Huang, Tsung-Ting Kuo, Wei-Chi Lai, Ming-Han Yang, Jung-Jung Yeh, Chun-Chao Yen, and Shou-De Lin, "Learning to Improve Area-Under-FROC for Imbalanced Medical Data Classification Using an Ensemble Method," in ACM SIGKDD Explorations, Vol. 10, Issue 2, 2008.
- Shou-De Lin and Kevin Knight, "Discovering the linear writing order of a two-dimensional ancient hieroglyphic script," in Artificial Intelligence, v.170/4-5, Elsevier, 2006. (One of the Top 25 hottest papers in Artificial Intelligence in 2006)
- Shou-De Lin and Craig Knoblock, "SERGEANT: A Framework for Building More Flexible Web Agents by Exploiting a Search Engine," in Journal of Web Intelligence and Agent Systems, v3(1), 2005.
- Shou-De Lin and Hans Chalupsky, "Using Unsupervised Link Discovery Methods to Find Interesting Facts and Connections in a Bibliography Dataset," in KDD Explorations, V5 Issue 2. (2nd place for the open task in ACM KDDCup 2003)
- Shou-De Lin and Hans Chalupsky, "Unsupervised Link Discovery in Multi-relational Data via Rarity Analysis," in Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003).
2009
- Cheng-Te Li and Shou-De Lin, "Egocentric Information Abstraction for Heterogeneous Social Networks," in ASONAM 2009.
- H.-Y. Lo, K.-W. Chang, S.-T. Chen, T.-H. Chiang, C.-S. Ferng, C.-J. Hsieh, Y.-K. Ko, T.-T. Kuo, H.-C. Lai, K.-Y. Lin, C.-H. Wang, H.-F. Yu, C.-J. Lin, H.-T. Lin, and S.-D. Lin, "An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naive Bayes," in Journal of Machine Learning Research, Workshop and Conference Proceedings, 2009.
Before 2008
- Shou-De Lin and Karin Verspoor, "A Semantics-Enhanced Language Model for Unsupervised Word Sense Disambiguation," in CICLing 2008.
- Shou-De Lin, "Modelling, Searching and Explaining Interesting Instances in Multi-Relational Network," in Ph.D. dissertation, 2006.
- Shou-De Lin, "Generating natural language description for paths in the semantic network, master final project report," in USC Linguistics Department, 2006.
- Shou-De Lin, "Interesting Instance Discovery in Multi-relational Data," in Proceedings of AAAI 2004 Doctoral Consortium, San Jose.
- Shou-De Lin and Hans Chalupsky, "Issues of Verification for Unsupervised Discovery Systems," in KDD 2004 Workshop on Link Discovery.
- Shou-De Lin and Craig Knoblock, "Exploiting a Search Engine to Develop More Flexible Web Agents," in Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence (WI 2003), Halifax, Canada.
- Michael P. Wellman, Peter R. Wurman, Kevin O'Malley, Roshan Bangera, Shou-De Lin, Daniel Reeves, and William E. Walsh, "Designing the Market Game for a Trading Agent Competition," in IEEE Internet Computing, 2001.
Tutorials
2009~2013
- Shou-De Lin, Mi-Yen Yeh, and Cheng-Te Li, "Sampling and Summarization for Social Networks," in PAKDD 2013.
- Shou-De Lin, Mi-Yen Yeh, and Cheng-Te Li, "Sampling and Summarization for Social Networks," in SDM 2013.
- Shou-De Lin, Hung-Yi Lo, and Cheng-Te Li, "Issues of Mining for Heterogeneous Social Networks," in PAKDD 2009.
Book Chapter
2010
- Cheng-Te Li and Shou-De Lin, "Mining Heterogeneous Social Networks for Egocentric Information Abstraction," in Lecture Notes in Social Networks, entitled "Social Networks Analysis and Mining: Foundations and Applications," Springer, 2010.
Newspaper
2008
- Hung-Yi Lo, Chun-Min Chang, Tsung-Hsien Chiang, Cho-Yi Hsiao, Anta Huang, Tsung-Ting Kuo, Wei-Chi Lai, Ming-Han Yang, Jung-Jung Yeh, Chun-Chao Yen, and Shou-De Lin, "Learning to Improve Area-UnderFROC for Imbalanced Medical Data Classification Using an Ensemble Method," in SIGKDD Explorations, 10(2), pp. 43-46, December 2008. (Invited Paper of KDD Cup 2008 Winner)