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ORCIDShou-De Lin
Shou-de Lin – Shoude Lin – 林守德
Person information
- affiliation: National Taiwan University
- unicode name: 林守德
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2020 – today
- 2024
[j32]Chao-Min Chang, Cheng-Te Li, Shou-De Lin:
Unilateral boundary time series forecasting. Frontiers Big Data 7 (2024)- [j31]Yu-Tung Pai
, Nien-En Sun, Cheng-Te Li, Shou-de Lin:
Incremental Data Drifting: Evaluation Metrics, Data Generation, and Approach Comparison. ACM Trans. Intell. Syst. Technol. 15(4): 71:1-71:26 (2024) - [c137]Yun-Da Tsai, Cayon Liow, Yin Sheng Siang, Shou-De Lin:
Toward More Generalized Malicious URL Detection Models. AAAI 2024: 21628-21636 - [c136]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: 4193-4205 - [c135]Tzu-Hsien Tsai, Yun-Da Tsai, Shou-De Lin:
lil'HDoC: An Algorithm for Good Arm Identification Under Small Threshold Gap. PAKDD (5) 2024: 78-89 - [c134]Yun-Da Tsai, Shou-De Lin:
Handling Concept Drift in Non-stationary Bandit Through Predicting Future Rewards. PAKDD (Workshops) 2024: 161-173 - [i27]Tzu-Hsien Tsai, Yun-Da Tsai, Shou-De Lin:
lil'HDoC: An Algorithm for Good Arm Identification under Small Threshold Gap. CoRR abs/2401.15879 (2024) - [i26]Yun-Da Tsai, Ting-Yu Yen, Pei-Fu Guo, Zhe-Yan Li, Shou-De Lin:
Text-centric Alignment for Multi-Modality Learning. CoRR abs/2402.08086 (2024) - [i25]Yun-Ang Wu, Yun-Da Tsai, Shou-De Lin:
LinearAPT: An Adaptive Algorithm for the Fixed-Budget Thresholding Linear Bandit Problem. CoRR abs/2403.06230 (2024) - [i24]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 abs/2406.10280 (2024) - [i23]Ting-Yu Yen, Yun-Da Tsai, Keng-Te Liao, Shou-De Lin:
Enhance the Robustness of Text-Centric Multimodal Alignments. CoRR abs/2407.05036 (2024) - [i22]Kerui Zhu, Bo-Wei Huang, Bowen Jin, Yizhu Jiao, Ming Zhong, Kevin Chang, Shou-De Lin, Jiawei Han:
Investigating Instruction Tuning Large Language Models on Graphs. CoRR abs/2408.05457 (2024) - [i21]Yun-Da Tsai, Ting-Yu Yen, Keng-Te Liao, Shou-De Lin:
Enhance Modality Robustness in Text-Centric Multimodal Alignment with Adversarial Prompting. CoRR abs/2408.09798 (2024) - [i20]Pei-Fu Guo, Yun-Da Tsai, Shou-De Lin:
Benchmarking Large Language Model Uncertainty for Prompt Optimization. CoRR abs/2409.10044 (2024) - 2023
- [j30]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): 105:1-105:26 (2023) - [c133]Cayon Liow, Cheng-Te Li, Chun-Pai Yang, Shou-De Lin:
Pseudo Triplet Networks for Classification Tasks with Cross-Source Feature Incompleteness. CIKM 2023: 4079-4083 - [c132]Karandeep Singh, Yu-Che Tsai, Cheng-Te Li, Meeyoung Cha, Shou-De Lin:
GraphFC: Customs Fraud Detection with Label Scarcity. CIKM 2023: 4829-4835 - [c131]Yiquan Jiang, Kengte Liao, Shoude Lin, Hongming Qiao, Kefeng Yu, Chengwei Yang, Yinqi Chen:
Self-supervised Multimodal Representation Learning for Product Identification and Retrieval. ICONIP (11) 2023: 579-594 - [c130]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: 53-65 - [i19]Yun-Da Tsai, Tzu-Hsien Tsai, Shou-De Lin:
Differential Good Arm Identification. CoRR abs/2303.07154 (2023) - [i18]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 abs/2303.15072 (2023) - [i17]Karandeep Singh, Yu-Che Tsai, Cheng-Te Li, Meeyoung Cha, Shou-De Lin:
GraphFC: Customs Fraud Detection with Label Scarcity. CoRR abs/2305.11377 (2023) - [i16]Bo-Wei Huang, Keng-Te Liao, Chang-Sheng Kao, Shou-De Lin:
Environment Diversification with Multi-head Neural Network for Invariant Learning. CoRR abs/2308.08778 (2023) - [i15]Yun-Da Tsai, Yu-Che Tsai, Bo-Wei Huang, Chun-Pai Yang, Shou-De Lin:
AutoML-GPT: Large Language Model for AutoML. CoRR abs/2309.01125 (2023) - [i14]Pei-Fu Guo, Ying-Hsuan Chen, Yun-Da Tsai, Shou-De Lin:
Towards Optimizing with Large Language Models. CoRR abs/2310.05204 (2023) - [i13]Felix Liawi, Yun-Da Tsai, Guan-Lun Lu, Shou-De Lin:
PSGText: Stroke-Guided Scene Text Editing with PSP Module. CoRR abs/2310.13366 (2023) - [i12]Eric L. Lee, Tsung-Ting Kuo, Shou-De Lin:
A Collaborative Filtering-Based Two Stage Model with Item Dependency for Course Recommendation. CoRR abs/2311.00612 (2023) - 2022
- [j29]Keng-Te Liao, Bo-Wei Huang, Chih-Chun Yang, Shou-De Lin:
Bayesian mixture variational autoencoders for multi-modal learning. Mach. Learn. 111(12): 4329-4357 (2022) - [c129]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: 1-9 - [c128]Yen-Ting Lee, Cheng-Te Li, Shou-De Lin:
Conditional Sentence Rephrasing without Parallel Training Corpus. ICME Workshops 2022: 1 - [c127]Bo-Wei Huang, Keng-Te Liao, Chang-Sheng Kao, Shou-De Lin:
Environment Diversification with Multi-head Neural Network for Invariant Learning. NeurIPS 2022 - [c126]Chih-Chun Yang, Cheng-Te Li, Shou-De Lin:
SMITH: A Self-supervised Downstream-Aware Framework for Missing Testing Data Handling. PAKDD (2) 2022: 499-510 - [i11]Yun-Da Tsai, Shou-De Lin:
Fast online inference for nonlinear contextual bandit based on Generative Adversarial Network. CoRR abs/2202.08867 (2022) - [i10]Yun-Da Tsai, Cayon Liow, Yin Sheng Siang, Shou-De Lin:
Toward more generalized Malicious URL Detection Models. CoRR abs/2202.10027 (2022) - 2021
- [j28]Chih-Te Lai, Cheng-Te Li, Shou-De Lin:
Deep Energy Factorization Model for Demographic Prediction. ACM Trans. Intell. Syst. Technol. 12(1): 8:1-8:16 (2021) - [c125]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: 4165-4172 - 2020
- [j27]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): 4277-4296 (2020) - [c124]Hong-You Chen, Sz-Han Yu, Shou-de Lin:
Glyph2Vec: Learning Chinese Out-of-Vocabulary Word Embedding from Glyphs. ACL 2020: 2865-2871 - [c123]Chin-Hui Chen, Yi-Fu Fu, Hsiao-Hua Cheng, Shou-De Lin:
Unseen Filler Generalization In Attention-based Natural Language Reasoning Models. CogMI 2020: 42-51 - [c122]Keng-Te Liao, Zhihong Shen, Chiyuan Huang, Chieh-Han Wu, Po-Chun Chen, Kuansan Wang, Shou-de Lin:
Explainable and Sparse Representations of Academic Articles for Knowledge Exploration. COLING 2020: 6207-6216 - [c121]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: 2086-2090 - [c120]Keng-Te Liao, Cheng-Syuan Lee, Zhong-Yu Huang, Shou-de Lin:
Explaining Word Embeddings via Disentangled Representation. AACL/IJCNLP 2020: 720-725
2010 – 2019
- 2019
- [j26]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): 474-498 (2019) - [j25]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: 49 (2019) - [j24]Jia-Yun Jiang, Cheng-Te Li, Shou-De Lin:
Towards a more reliable privacy-preserving recommender system. Inf. Sci. 482: 248-265 (2019) - [c119]Jun-Kun Wang, Chi-Jen Lu, Shou-De Lin:
Online Linear Optimization with Sparsity Constraints. ALT 2019: 882-896 - [c118]Fan-Yun Sun, Yen-Yu Chang, Yueh-Hua Wu, Shou-De Lin:
A Regulation Enforcement Solution for Multi-agent Reinforcement Learning. AAMAS 2019: 2201-2203 - [c117]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: 1-8 - [c116]Sakura Yamaki, Shou-de Lin, Wataru Kameyama:
Detection of Anomaly State Caused by Unexpected Accident using Data of Smart Card for Public Transportation. IEEE BigData 2019: 1693-1698 - [c115]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: 11-20 - [c114]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: 43-48 - [c113]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: 3577-3582 - [c112]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: 2031-2041 - [c111]Hong-You Chen, Chin-Hua Hu, Leila Wehbe, Shou-De Lin:
Self-Discriminative Learning for Unsupervised Document Embedding. NAACL-HLT (1) 2019: 2465-2474 - [c110]Chao-Chung Wu, Ruihua Song, Tetsuya Sakai, Wen-Feng Cheng, Xing Xie, Shou-De Lin:
Evaluating Image-Inspired Poetry Generation. NLPCC (1) 2019: 539-551 - [c109]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: 4:1-4:5 - [c108]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: 470-479 - [i9]Fan-Yun Sun, Yen-Yu Chang, Yueh-Hua Wu, Shou-De Lin:
A Regulation Enforcement Solution for Multi-agent Reinforcement Learning. CoRR abs/1901.10059 (2019) - [i8]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 abs/1905.04874 (2019) - [i7]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 abs/1909.07683 (2019) - 2018
- [j23]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): 33-45 (2018) - [j22]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): 2228-2241 (2018) - [c107]Yueh-Hua Wu, Shou-De Lin:
A Low-Cost Ethics Shaping Approach for Designing Reinforcement Learning Agents. AAAI 2018: 1687-1694 - [c106]Fan-Yun Sun, Yen-Yu Chang, Yueh-Hua Wu, Shou-De Lin:
Designing Non-greedy Reinforcement Learning Agents with Diminishing Reward Shaping. AIES 2018: 297-302 - [c105]Hong-You Chen, Cheng-Syuan Lee, Keng-Te Liao, Shou-de Lin:
Word Relation Autoencoder for Unseen Hypernym Extraction Using Word Embeddings. EMNLP 2018: 4834-4839 - [c104]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: 2651-2655 - [c103]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: 10891-10899 - [c102]Fang-Yi Chang, Chun Chen, Shou-De Lin:
An Empirical Study of Ladder Network and Multitask Learning on Energy Disaggregation in Taiwan. TAAI 2018: 86-89 - [c101]Yian Chen, Xing Xie, Shou-De Lin, Arden Chiu:
WSDM Cup 2018: Music Recommendation and Churn Prediction. WSDM 2018: 8-9 - [r2]Cheng-Te Li, Hsun-Ping Hsieh, Tsung-Ting Kuo, Shou-De Lin:
Opinion Diffusion and Analysis on Social Networks. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i6]Yen-Yu Chang, Fan-Yun Sun, Yueh-Hua Wu, Shou-De Lin:
A Memory-Network Based Solution for Multivariate Time-Series Forecasting. CoRR abs/1809.02105 (2018) - [i5]Yueh-Hua Wu, Fan-Yun Sun, Yen-Yu Chang, Shou-De Lin:
ANS: Adaptive Network Scaling for Deep Rectifier Reinforcement Learning Models. CoRR abs/1809.02112 (2018) - [i4]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 abs/1810.08765 (2018) - 2017
- [c100]Hao-Ying Liang, Yun-Tung Shieh, Addicam Sanjay, Shao-Wen Yang, Shou-De Lin:
Ensemble-Based Location Tracking Using Passive RFID. DSAA 2017: 420-428 - [c99]Eric L. Lee, Tsung-Ting Kuo, Shou-De Lin:
A Collaborative Filtering-Based Two Stage Model with Item Dependency for Course Recommendation. DSAA 2017: 496-503 - [c98]Ian En-Hsu Yen, Wei-Cheng Lee, Sung-En Chang, Arun Sai Suggala, Shou-De Lin, Pradeep Ravikumar:
Latent Feature Lasso. ICML 2017: 3949-3957 - [c97]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: 5257-5266 - [c96]Hao-En Sung, Cheng-Kuan Chen, Han Xiao, Shou-De Lin:
A Classification Model for Diverse and Noisy Labelers. PAKDD (1) 2017: 58-69 - [c95]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: 771-779 - [i3]Jia-Yun Jiang, Cheng-Te Li, Shou-De Lin:
Towards a More Reliable Privacy-preserving Recommender System. CoRR abs/1711.07638 (2017) - [i2]Yueh-Hua Wu, Shou-De Lin:
A Low-Cost Ethics Shaping Approach for Designing Reinforcement Learning Agents. CoRR abs/1712.04172 (2017) - 2016
- [j21]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) - [c94]Jun-Kun Wang, Shou-De Lin:
Parallel Least-Squares Policy Iteration. DSAA 2016: 166-173 - [c93]Jun-Kun Wang, Shou-De Lin:
Efficient Sampling-Based ADMM for Distributed Data. DSAA 2016: 321-330 - [c92]Yu-Yang Huang, Shou-De Lin:
Transferring User Interests Across Websites with Unstructured Text for Cold-Start Recommendation. EMNLP 2016: 805-814 - [c91]Chia-Hsin Ting, Hung-Yi Lo, Shou-De Lin:
Transfer-Learning Based Model for Reciprocal Recommendation. PAKDD (2) 2016: 491-502 - [c90]Chi-Ruei Li, Addicam Sanjay, Shao-Wen Yang, Shou-De Lin:
Transfer learning for sequential recommendation model. TAAI 2016: 154-161 - [i1]Guang-He Lee, Shao-Wen Yang, Shou-De Lin:
Toward Implicit Sample Noise Modeling: Deviation-driven Matrix Factorization. CoRR abs/1610.09274 (2016) - 2015
- [j20]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) - [j19]Cheng-Te Li, Man-Kwan Shan, Shou-De Lin:
On team formation with expertise query in collaborative social networks. Knowl. Inf. Syst. 42(2): 441-463 (2015) - [c89]San-Chuan Hung, Tsung-Ting Kuo, Shou-De Lin:
Novel Topic Diffusion Prediction using Latent Semantic and User Behavior. ASE BD&SI 2015: 39:1-39:6 - [c88]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: 381-390 - [c87]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: 551-560 - [c86]Yen-Kai Wang, Wei-Ming Chen, Cheng-Te Li, Shou-De Lin:
Identifying smallest unique subgraphs in a heterogeneous social network. IEEE BigData 2015: 757-766 - [c85]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: 1-10 - [c84]Guang-He Lee, Shou-De Lin:
LambdaMF: Learning Nonsmooth Ranking Functions in Matrix Factorization Using Lambda. ICDM 2015: 823-828 - [c83]Hsun-Ping Hsieh, Cheng-Te Li, Shou-De Lin:
Measuring and Recommending Time-Sensitive Routes from Location-based Data. IJCAI 2015: 4193-4196 - [c82]Hsun-Ping Hsieh, Shou-De Lin, Yu Zheng:
Inferring Air Quality for Station Location Recommendation Based on Urban Big Data. KDD 2015: 437-446 - [c81]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: 695-704 - [c80]Ian En-Hsu Yen, Shan-Wei Lin, Shou-De Lin:
A Dual Augmented Block Minimization Framework for Learning with Limited Memory. NIPS 2015: 3582-3590 - [c79]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: 576-592 - [e4]Shou-de Lin, Lun-Wei Ku, Cheng-Te Li, Erik Cambria:
Proceedings of the third International Workshop on Natural Language Processing for Social Media, SocialNLP@NAACL 2015, Denver, Colorado, USA, June 5, 2015. Association for Computational Linguistics 2015, ISBN 978-1-941643-48-8 [contents] - 2014
- [j18]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) - [j17]Hsun-Ping Hsieh, Cheng-Te Li, Shou-De Lin:
Measuring and Recommending Time-Sensitive Routes from Location-Based Data. ACM Trans. Intell. Syst. Technol. 5(3): 45:1-45:27 (2014) - [j16]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): 1679-1691 (2014) - [c78]Yu-Yang Huang, Rui Yan, Tsung-Ting Kuo, Shou-De Lin:
Enriching Cold Start Personalized Language Model Using Social Network Information. ACL (2) 2014: 611-617 - [c77]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: 265-272 - [c76]Jung-Jung Yeh, Tsung-Ting Kuo, William Chen, Shou-De Lin:
Minimizing expected loss for risk-avoiding reinforcement learning. DSAA 2014: 11-17 - [c75]Cho-Yi Hsiao, Hung-Yi Lo, Tu-Chun Yin, Shou-De Lin:
Optimizing specificity under perfect sensitivity for medical data classification. DSAA 2014: 163-169 - [c74]How Jing, Shou-De Lin:
Neural Conditional Energy Models for Multi-label Classification. ICDM 2014: 240-249 - [c73]How Jing, An-Chun Liang, Shou-De Lin, Yu Tsao:
A Transfer Probabilistic Collective Factorization Model to Handle Sparse Data in Collaborative Filtering. ICDM 2014: 250-259 - [c72]Hsun-Ping Hsieh, Cheng-Te Li, Shou-De Lin:
Trip Router: A Time-Sensitive Route Recommender System. ICDM Workshops 2014: 1207-1210 - [c71]Jun-Kun Wang, Shou-de Lin:
Robust Inverse Covariance Estimation under Noisy Measurements. ICML 2014: 928-936 - [c70]Chih-Hung Hsieh, Hsin-Mu Tsai, Shao-Wen Yang, Shou-De Lin:
Predict Scooter's Stopping Event Using Smartphone as the Sensing Device. iThings/GreenCom/CPSCom 2014: 17-23 - [c69]Chung-Yi Li, Shou-De Lin:
Matching users and items across domains to improve the recommendation quality. KDD 2014: 801-810 - [c68]