Shou-De Lin

ORCID

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 90

Top Venues

Publications

Yun-Da Tsai, Ting-Yu Yen, Pei-Fu Guo, Zhe-Yan Li, Shou-De Lin
Text-centric Alignment for Multi-Modality Learning. CoRR (2024)
Tzu-Hsien Tsai, Yun-Da Tsai, Shou-De Lin
lil'HDoC: An Algorithm for Good Arm Identification Under Small Threshold Gap. PAKDD (5) (2024)
Yun-Da Tsai, Shou-De Lin
Handling Concept Drift in Non-stationary Bandit Through Predicting Future Rewards. PAKDD (Workshops) (2024)
Chao-Min Chang, Cheng-Te Li, Shou-De Lin
Unilateral boundary time series forecasting. Frontiers Big Data 7 (2024)
Tzu-Hsien Tsai, Yun-Da Tsai, Shou-De Lin
lil'HDoC: An Algorithm for Good Arm Identification under Small Threshold Gap. CoRR (2024)
Yu-Hsiang Huang, Yu-Che Tsai, Hsiang Hsiao, Hong-Yi Lin, Shou-De Lin
Transferable Embedding Inversion Attack: Uncovering Privacy Risks in Text Embeddings without Model Queries. CoRR (2024)
Yu-Hsiang Huang, Yu-Che Tsai, Hsiang Hsiao, Hong-Yi Lin, Shou-De Lin
Transferable Embedding Inversion Attack: Uncovering Privacy Risks in Text Embeddings without Model Queries. ACL (1) (2024)
Yun-Da Tsai, Cayon Liow, Yin Sheng Siang, Shou-De Lin
Toward More Generalized Malicious URL Detection Models. AAAI (2024)
Yun-Ang Wu, Yun-Da Tsai, Shou-De Lin
LinearAPT: An Adaptive Algorithm for the Fixed-Budget Thresholding Linear Bandit Problem. CoRR (2024)
Ting-Yu Yen, Yun-Da Tsai, Keng-Te Liao, Shou-De Lin
Enhance the Robustness of Text-Centric Multimodal Alignments. CoRR (2024)
Yun-Da Tsai, Tzu-Hsien Tsai, Shou-De Lin
Differential Good Arm Identification. CoRR (2023)
Karandeep Singh, Yu-Che Tsai, Cheng-Te Li, Meeyoung Cha, Shou-De Lin
GraphFC: Customs Fraud Detection with Label Scarcity. CoRR (2023)
Karandeep Singh, Yu-Che Tsai, Cheng-Te Li, Meeyoung Cha, Shou-De Lin
GraphFC: Customs Fraud Detection with Label Scarcity. CIKM (2023)
Eric L. Lee, Tsung-Ting Kuo, Shou-De Lin
A Collaborative Filtering-Based Two Stage Model with Item Dependency for Course Recommendation. CoRR (2023)
Chu-Chen Li, Cheng-Te Li, Shou-De Lin
Learning Privacy-Preserving Embeddings for Image Data to Be Published. ACM Trans. Intell. Syst. Technol. 14 (6) (2023)
Pei-Fu Guo, Ying-Hsuan Chen, Yun-Da Tsai, Shou-De Lin
Towards Optimizing with Large Language Models. CoRR (2023)
Felix Liawi, Yun-Da Tsai, Guan-Lun Lu, Shou-De Lin
PSGText: Stroke-Guided Scene Text Editing with PSP Module. CoRR (2023)
Bo-Wei Huang, Keng-Te Liao, Chang-Sheng Kao, Shou-De Lin
Environment Diversification with Multi-head Neural Network for Invariant Learning. CoRR (2023)
Yen-Ching Tseng, Zu-Mu Chen, Mi-Yen Yeh, Shou-De Lin
UPGAT: Uncertainty-Aware Pseudo-neighbor Augmented Knowledge Graph Attention Network. PAKDD (2) (2023)
Cayon Liow, Cheng-Te Li, Chun-Pai Yang, Shou-De Lin
Pseudo Triplet Networks for Classification Tasks with Cross-Source Feature Incompleteness. CIKM (2023)
Yun-Da Tsai, Yu-Che Tsai, Bo-Wei Huang, Chun-Pai Yang, Shou-De Lin
AutoML-GPT: Large Language Model for AutoML. CoRR (2023)
Yi-Ting Lee, Da-Yi Wu, Chih-Chun Yang, Shou-De Lin
Exposing the Functionalities of Neurons for Gated Recurrent Unit Based Sequence-to-Sequence Model. CoRR (2023)
Yun-Da Tsai, Cayon Liow, Yin Sheng Siang, Shou-De Lin
Toward more generalized Malicious URL Detection Models. CoRR (2022)
Yun-Da Tsai, Shou-De Lin
Fast online inference for nonlinear contextual bandit based on Generative Adversarial Network. CoRR (2022)
Yen-Ting Lee, Cheng-Te Li, Shou-De Lin
Conditional Sentence Rephrasing without Parallel Training Corpus. ICME Workshops (2022)
Keng-Te Liao, Bo-Wei Huang, Chih-Chun Yang, Shou-De Lin
Bayesian mixture variational autoencoders for multi-modal learning. Mach. Learn. 111 (12) (2022)
Ta-Chun Shen, Chun-Pai Yang, Ian En-Hsu Yen, Shou-De Lin
Towards ℓ1 Regularization for Deep Neural Networks: Model Sparsity Versus Task Difficulty. DSAA (2022)
Chih-Chun Yang, Cheng-Te Li, Shou-De Lin
SMITH: A Self-supervised Downstream-Aware Framework for Missing Testing Data Handling. PAKDD (2) (2022)
Bo-Wei Huang, Keng-Te Liao, Chang-Sheng Kao, Shou-De Lin
Environment Diversification with Multi-head Neural Network for Invariant Learning. NeurIPS (2022)
Yun-Da Tsai, Cheng-Kuan Chen, Shou-De Lin
Toward an Effective Black-Box Adversarial Attack on Functional JavaScript Malware against Commercial Anti-Virus. CIKM (2021)
Chih-Te Lai, Cheng-Te Li, Shou-De Lin
Deep Energy Factorization Model for Demographic Prediction. ACM Trans. Intell. Syst. Technol. 12 (1) (2021)
Chin-Hui Chen, Yi-Fu Fu, Hsiao-Hua Cheng, Shou-De Lin
Unseen Filler Generalization In Attention-based Natural Language Reasoning Models. CogMI (2020)
Yu-Sheng Chou, Chien-Yao Wang, Shou-De Lin, Hong-Yuan Mark Liao
How Incompletely Segmented Information Affects Multi-Object Tracking and Segmentation (MOTS). ICIP (2020)
Shu-Kai Zhang, Cheng-Te Li, Shou-De Lin
A joint optimization framework for better community detection based on link prediction in social networks. Knowl. Inf. Syst. 62 (11) (2020)
Kung-Hsiang Huang, Yi-Fu Fu, Yi-Ting Lee, Tzong-Hann Lee, Yao-Chun Chan, Yi-Hui Lee, Shou-De Lin
A-HA: a hybrid approach for hotel recommendation. RecSys Challenge (2019)
Chih-Te Lai, Yi-Te Hong, Hong-You Chen, Chi-Jen Lu, Shou-De Lin
Multiple Text Style Transfer by using Word-level Conditional Generative Adversarial Network with Two-Phase Training. EMNLP/IJCNLP (1) (2019)
Szu-Wei Fu, Chien-Feng Liao, Yu Tsao, Shou-De Lin
MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement. ICML (2019)
Ming-Han Feng, Chin-Chi Hsu, Cheng-Te Li, Mi-Yen Yeh, Shou-De Lin
MARINE: Multi-relational Network Embeddings with Relational Proximity and Node Attributes. WWW (2019)
Yue Liu, Helena Lee, Palakorn Achananuparp, Ee-Peng Lim, Tzu-Ling Cheng, Shou-De Lin
Characterizing and Predicting Repeat Food Consumption Behavior for Just-in-Time Interventions. CoRR (2019)
Yu-Sheng Chou, Chien-Yao Wang, Ming-Chiao Chen, Shou-De Lin, Hong-Yuan Mark Liao
Dynamic Gallery for Real-Time Multi-Target Multi-Camera Tracking. AVSS (2019)
Hong-You Chen, Chin-Hua Hu, Leila Wehbe, Shou-De Lin
Self-Discriminative Learning for Unsupervised Document Embedding. NAACL-HLT (1) (2019)
Yi-An Lai, Chin-Chi Hsu, Wen-Hao Chen, Mi-Yen Yeh, Shou-De Lin
DeepRank: improving unsupervised node ranking via link discovery. Data Min. Knowl. Discov. 33 (2) (2019)
Fan-Yun Sun, Yen-Yu Chang, Yueh-Hua Wu, Shou-De Lin
A Regulation Enforcement Solution for Multi-agent Reinforcement Learning. CoRR (2019)
Szu-Wei Fu, Chien-Feng Liao, Yu Tsao, Shou-De Lin
MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement. CoRR (2019)
Fan-Yun Sun, Yen-Yu Chang, Yueh-Hua Wu, Shou-De Lin
A Regulation Enforcement Solution for Multi-agent Reinforcement Learning. AAMAS (2019)
Jun-Kun Wang, Chi-Jen Lu, Shou-De Lin
Online Linear Optimization with Sparsity Constraints. ALT (2019)
Chao-Chung Wu, Ruihua Song, Tetsuya Sakai, Wen-Feng Cheng, Xing Xie, Shou-De Lin
Evaluating Image-Inspired Poetry Generation. NLPCC (1) (2019)
Jia-Yun Jiang, Cheng-Te Li, Shou-De Lin
Towards a more reliable privacy-preserving recommender system. Inf. Sci. 482 (2019)
Yue Liu, Helena Lee, Palakorn Achananuparp, Ee-Peng Lim, Tzu-Ling Cheng, Shou-De Lin
Characterizing and Predicting Repeat Food Consumption Behavior for Just-in-Time Interventions. PDH (2019)
Liang-Hsin Shen, Pei-Lun Tai, Chao-Chung Wu, Shou-De Lin
Controlling Sequence-to-Sequence Models - A Demonstration on Neural-based Acrostic Generator. EMNLP/IJCNLP (3) (2019)
Wen-Hao Chen, Chin-Chi Hsu, Yi-An Lai, Vincent Liu, Mi-Yen Yeh, Shou-De Lin
Attribute-Aware Recommender System Based on Collaborative Filtering: Survey and Classification. Frontiers Big Data 2 (2019)
Fang-Yi Chang, Chun Chen, Shou-De Lin
An Empirical Study of Ladder Network and Multitask Learning on Energy Disaggregation in Taiwan. TAAI (2018)
Fan-Yun Sun, Yen-Yu Chang, Yueh-Hua Wu, Shou-De Lin
Designing Non-greedy Reinforcement Learning Agents with Diminishing Reward Shaping. AIES (2018)
Yian Chen, Xing Xie, Shou-De Lin, Arden Chiu
WSDM Cup 2018: Music Recommendation and Churn Prediction. WSDM (2018)
Yu-Sheng Chou, Pai-Heng Hsiao, Shou-De Lin, Hong-Yuan Mark Liao
How Sampling Rate Affects Cross-Domain Transfer Learning for Video Description. ICASSP (2018)
Ian En-Hsu Yen, Wei-Cheng Lee, Kai Zhong, Sung-En Chang, Pradeep Ravikumar, Shou-De Lin
MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization. NeurIPS (2018)
Chin-Chi Hsu, Mi-Yen Yeh, Shou-De Lin
A General Framework for Implicit and Explicit Social Recommendation. IEEE Trans. Knowl. Data Eng. 30 (12) (2018)
Wen-Hao Chen, Chin-Chi Hsu, Yi-An Lai, Vincent Liu, Mi-Yen Yeh, Shou-De Lin
Attribute-aware Collaborative Filtering: Survey and Classification. CoRR (2018)
Yueh-Hua Wu, Shou-De Lin
A Low-Cost Ethics Shaping Approach for Designing Reinforcement Learning Agents. AAAI (2018)
Cheng-Te Li, Shou-De Lin
Social Flocks: Simulating Crowds to Discover the Connection Between Spatial-Temporal Movements of People and Social Structure. IEEE Trans. Comput. Soc. Syst. 5 (1) (2018)
Yen-Yu Chang, Fan-Yun Sun, Yueh-Hua Wu, Shou-De Lin
A Memory-Network Based Solution for Multivariate Time-Series Forecasting. CoRR (2018)
Yueh-Hua Wu, Fan-Yun Sun, Yen-Yu Chang, Shou-De Lin
ANS: Adaptive Network Scaling for Deep Rectifier Reinforcement Learning Models. CoRR (2018)
Yi-An Lai, Chin-Chi Hsu, Wen-Hao Chen, Mi-Yen Yeh, Shou-De Lin
PRUNE: Preserving Proximity and Global Ranking for Network Embedding. NIPS (2017)
Hao-En Sung, Cheng-Kuan Chen, Han Xiao, Shou-De Lin
A Classification Model for Diverse and Noisy Labelers. PAKDD (1) (2017)
Ian En-Hsu Yen, Wei-Cheng Lee, Sung-En Chang, Arun Sai Suggala, Shou-De Lin, Pradeep Ravikumar
Latent Feature Lasso. ICML (2017)
Jia-Yun Jiang, Cheng-Te Li, Shou-De Lin
Towards a More Reliable Privacy-preserving Recommender System. CoRR (2017)
Hao-Ying Liang, Yun-Tung Shieh, Addicam Sanjay, Shao-Wen Yang, Shou-De Lin
Ensemble-Based Location Tracking Using Passive RFID. DSAA (2017)
Chin-Chi Hsu, Yi-An Lai, Wen-Hao Chen, Ming-Han Feng, Shou-De Lin
Unsupervised Ranking using Graph Structures and Node Attributes. WSDM (2017)
Eric L. Lee, Tsung-Ting Kuo, Shou-De Lin
A Collaborative Filtering-Based Two Stage Model with Item Dependency for Course Recommendation. DSAA (2017)
Yueh-Hua Wu, Shou-De Lin
A Low-Cost Ethics Shaping Approach for Designing Reinforcement Learning Agents. CoRR (2017)
Jun-Kun Wang, Shou-De Lin
Efficient Sampling-Based ADMM for Distributed Data. DSAA (2016)
Jun-Kun Wang, Shou-De Lin
Parallel Least-Squares Policy Iteration. DSAA (2016)
Chi-Ruei Li, Addicam Sanjay, Shao-Wen Yang, Shou-De Lin
Transfer learning for sequential recommendation model. TAAI (2016)
Yu-Yang Huang, Rui Yan, Tsung-Ting Kuo, Shou-De Lin
Enriching Cold Start Personalized Language Model Using Social Network Information. Int. J. Comput. Linguistics Chin. Lang. Process. 21 (1) (2016)
Yu-Yang Huang, Shou-De Lin
Transferring User Interests Across Websites with Unstructured Text for Cold-Start Recommendation. EMNLP (2016)
Chia-Hsin Ting, Hung-Yi Lo, Shou-De Lin
Transfer-Learning Based Model for Reciprocal Recommendation. PAKDD (2) (2016)
Guang-He Lee, Shao-Wen Yang, Shou-De Lin
Toward Implicit Sample Noise Modeling: Deviation-driven Matrix Factorization. CoRR (2016)
Han Xiao, Shou-De Lin, Mi-Yen Yeh, Phillip B. Gibbons, Claudia Eckert
Learning better while sending less: Communication-efficient online semi-supervised learning in client-server settings. DSAA (2015)
Hsun-Ping Hsieh, Shou-De Lin, Yu Zheng
Inferring Air Quality for Station Location Recommendation Based on Urban Big Data. KDD (2015)
Cheng-Te Li, Man-Kwan Shan, Shou-De Lin
On team formation with expertise query in collaborative social networks. Knowl. Inf. Syst. 42 (2) (2015)
Guang-He Lee, Shou-De Lin
LambdaMF: Learning Nonsmooth Ranking Functions in Matrix Factorization Using Lambda. ICDM (2015)
Su-Chen Lin, Shou-De Lin, Ming-Syan Chen
A Learning-based Framework to Handle Multi-round Multi-party Influence Maximization on Social Networks. KDD (2015)
Hsun-Ping Hsieh, Cheng-Te Li, Shou-De Lin
Estimating Potential Customers Anywhere and Anytime Based on Location-Based Social Networks. ECML/PKDD (2) (2015)
San-Chuan Hung, Tsung-Ting Kuo, Shou-De Lin
Novel Topic Diffusion Prediction using Latent Semantic and User Behavior. ASE BD&SI (2015)
Chin-Chi Hsu, Perng-Hwa Kung, Mi-Yen Yeh, Shou-De Lin, Phillip B. Gibbons
Bandwidth-efficient distributed k-nearest-neighbor search with dynamic time warping. IEEE BigData (2015)
Hsun-Ping Hsieh, Cheng-Te Li, Shou-De Lin
Measuring and Recommending Time-Sensitive Routes from Location-based Data. IJCAI (2015)
Ian En-Hsu Yen, Shan-Wei Lin, Shou-De Lin
A Dual Augmented Block Minimization Framework for Learning with Limited Memory. NIPS (2015)
Chung-Yi Li, Wei-Lun Su, Todd G. McKenzie, Fu-Chun Hsu, Shou-De Lin, Jane Yung-jen Hsu, Phillip B. Gibbons
Recommending missing sensor values. IEEE BigData (2015)
Yen-Kai Wang, Wei-Ming Chen, Cheng-Te Li, Shou-De Lin
Identifying smallest unique subgraphs in a heterogeneous social network. IEEE BigData (2015)
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 (2015)
Chung-Yi Li, Shou-De Lin
Matching users and items across domains to improve the recommendation quality. KDD (2014)
Wei-Shih Lin, Tsung-Ting Kuo, Yu-Yang Huang, Wan-Chen Lu, Shou-De Lin
A Transfer-Learning Approach to Exploit Noisy Information for Classification and Its Application on Sentiment Detection. TAAI (2014)
Chin-Hua Tsai, Jing-Kai Lou, Wan-Chen Lu, Shou-De Lin
Exploiting rank-learning models to predict the diffusion of preferences on social networks. ASONAM (2014)
Eric L. Lee, Jing-Kai Lou, Wei-Ming Chen, Yen-Chi Chen, Shou-De Lin, Yen-Sheng Chiang, Kuan-Ta Chen
Fairness-Aware Loan Recommendation for Microfinance Services. SocialCom (2014)
Chia-Jen Lin, Tsung-Ting Kuo, Shou-De Lin
A Content-Based Matrix Factorization Model for Recipe Recommendation. PAKDD (2) (2014)
Yu-Yang Huang, Yu-An Yen, Ting-Wei Ku, Shou-De Lin, Wen-Tai Hsieh, Tsun Ku
A Weight-Sharing Gaussian Process Model Using Web-Based Information for Audience Rating Prediction. TAAI (2014)
Hung-Yi Lo, Shou-De Lin, Hsin-Min Wang
Generalized k-Labelsets Ensemble for Multi-Label and Cost-Sensitive Classification. IEEE Trans. Knowl. Data Eng. 26 (7) (2014)
Yu-Yang Huang, Rui Yan, Tsung-Ting Kuo, Shou-De Lin
Enriching Cold Start Personalized Language Model Using Social Network Information. ACL (2) (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, Yi-Ping Hung
Connected vehicle safety science, system, and framework. WF-IoT (2014)
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) (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Shou-De Lin