A Near-optimal Solution for the Heterogeneous Multi-processor Single-level Voltage Setup Problem. - Tai-Yi Huang; Yu-Che Tsai; Edward T.-H. Chu (IPDPS, 2007)

An Efficient Real-Time Disk-Scheduling Framework with Adaptive Quality Guarantee. - Cheng-Han Tsai; Tai-Yi Huang; Edward T.-H. Chu; Chun-Hang Wei; Yu-Che Tsai (IEEE Trans. Computers, 2008)

An Optimal Solution for the Heterogeneous Multiprocessor Single-Level Voltage-Setup Problem. - Edward T.-H. Chu; Tai-Yi Huang; Yu-Che Tsai (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2009)

Variations in Connectivity in the Sensorimotor and Default-Mode Networks During the First Nocturnal Sleep Cycle. - Changwei W. Wu; Po-Yu Liu; Pei-Jung Tsai; Yu-Chin Wu; Ching-Sui Hung; Yu-Che Tsai; Kuan-Hung Cho; Bharat B. Biswal; Chia-Ju Chen; Ching-Po Lin (Brain Connect., 2012)

Query Embedding Learning for Context-based Social Search. - Yi-Chun Chen; Yu-Che Tsai; Cheng-Te Li (CIKM, 2019)

Predicting New Adopters via Socially-Aware Neural Graph Collaborative Filtering. - Yu-Che Tsai; Muzhi Guan; Cheng-Te Li; Meeyoung Cha; Yong Li 008; Yue Wang 007 (CSoNet, 2019)

FineNet: a joint convolutional and recurrent neural network model to forecast and recommend anomalous financial items. - Yu-Che Tsai; Chih-Yao Chen; Shao-Lun Ma; Pei-Chi Wang; You-Jia Chen; Yu-Chieh Chang; Cheng-Te Li (RecSys, 2019)

DATE: Dual Attentive Tree-aware Embedding for Customs Fraud Detection. - Sundong Kim; Yu-Che Tsai; Karandeep Singh; Yeonsoo Choi; Etim Ibok; Cheng-Te Li; Meeyoung Cha (KDD, 2020)

CARE: learning convolutional attentional recurrent embedding for sequential recommendation. - Yu-Che Tsai; Cheng-Te Li (ASONAM, 2021)

FinGAT: Financial Graph Attention Networks for Recommending Top-K Profitable Stocks. - Yi-Ling Hsu; Yu-Che Tsai; Cheng-Te Li (CoRR, 2021)

Unsupervised Post-Time Fake Social Message Detection with Recommendation-aware Representation Learning. - Shao-Ping Hsiao; Yu-Che Tsai; Cheng-Te Li (WWW (Companion Volume), 2022)

SocialNLP'22: 10th International Workshop on Natural Language Processing for Social Media. - Cheng-Te Li; Lun-Wei Ku; Yu-Che Tsai; Wei-Yao Wang (WWW (Companion Volume), 2022)

Development of parking space certificate management system based on blockchain approach. - Yu-Che Tsai; Ming-Te Chen; Yi-Ying Chang (BCD, 2023)

GraphFC: Customs Fraud Detection with Label Scarcity. - Karandeep Singh; Yu-Che Tsai; Cheng-Te Li; Meeyoung Cha; Shou-De Lin (CIKM, 2023)

Graph Neural Networks for Tabular Data Learning. - Cheng-Te Li; Yu-Che Tsai; Jay Chiehen Liao (ICDE, 2023)

Tutorials at The Web Conference 2023. - Valeria Fionda; Olaf Hartig; Reyhaneh Abdolazimi; Sihem Amer-Yahia; Hongzhi Chen; Xiao Chen 016; Peng Cui 001; Jeffrey Dalton 001; Xin Luna Dong; Lisette Espín-Noboa; Wenqi Fan; Manuela Fritz; et al. (WWW (Companion Volume), 2023)

AutoML-GPT: Large Language Model for AutoML. - Yun-Da Tsai; Yu-Che Tsai; Bo-Wei Huang; Chun-Pai Yang; Shou-De Lin (CoRR, 2023)

FinGAT: Financial Graph Attention Networks for Recommending Top-$K$K Profitable Stocks. - Yi-Ling Hsu; Yu-Che Tsai; Cheng-Te Li (IEEE Trans. Knowl. Data Eng., 2023)

Transferable Embedding Inversion Attack: Uncovering Privacy Risks in Text Embeddings without Model Queries. - Yu-Hsiang Huang; Yu-Che Tsai; Hsiang Hsiao; Hong-Yi Lin; Shou-De Lin (ACL (1), 2024)

The 12th International Workshop on Natural Language Processing for Social Media (SocialNLP 2024). - Cheng-Te Li; Lun-Wei Ku; Yu-Che Tsai (WWW (Companion Volume), 2024)

Burstiness-aware Bipartite Graph Neural Networks for Fraudulent User Detection on Rating Platforms. - Yen-Wen Lu; Yu-Che Tsai; Cheng-Te Li (WWW (Companion Volume), 2024)

Graph Neural Networks for Tabular Data Learning: A Survey with Taxonomy and Directions. - Cheng-Te Li; Yu-Che Tsai; Chih-Yao Chen; Jay Chiehen Liao (CoRR, 2024)