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2020 – today
- 2024
[j1]Zhen Yang
, Ming Ding, Tinglin Huang, Yukuo Cen, Junshuai Song, Bin Xu, Yuxiao Dong, Jie Tang:
Does Negative Sampling Matter? a Review With Insights Into its Theory and Applications. IEEE Trans. Pattern Anal. Mach. Intell. 46(8): 5692-5711 (2024)- [c12]Zhenqiao Song, Tinglin Huang, Lei Li, Wengong Jin:
SurfPro: Functional Protein Design Based on Continuous Surface. ICML 2024 - [i6]Zhen Yang, Ming Ding, Tinglin Huang, Yukuo Cen, Junshuai Song, Bin Xu, Yuxiao Dong, Jie Tang:
Does Negative Sampling Matter? A Review with Insights into its Theory and Applications. CoRR abs/2402.17238 (2024) - [i5]Zhenqiao Song, Tinglin Huang, Lei Li, Wengong Jin:
SurfPro: Functional Protein Design Based on Continuous Surface. CoRR abs/2405.06693 (2024) - 2023
- [c11]Zhen Yang, Tinglin Huang, Ming Ding, Yuxiao Dong, Rex Ying, Yukuo Cen, Yangliao Geng, Jie Tang:
BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs. KDD 2023: 3057-3069 - [c10]Tinglin Huang, Ziniu Hu, Rex Ying:
Learning to Group Auxiliary Datasets for Molecule. NeurIPS 2023 - [i4]Zhen Yang, Tinglin Huang, Ming Ding, Yuxiao Dong, Rex Ying, Yukuo Cen, Yangliao Geng, Jie Tang:
BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs. CoRR abs/2306.03355 (2023) - [i3]Tinglin Huang, Ziniu Hu, Rex Ying:
Learning to Group Auxiliary Datasets for Molecule. CoRR abs/2307.04052 (2023) - 2022
- [c9]Wenzheng Feng, Yuxiao Dong, Tinglin Huang, Ziqi Yin, Xu Cheng, Evgeny Kharlamov, Jie Tang:
GRAND+: Scalable Graph Random Neural Networks. WWW 2022: 3248-3258 - [i2]Wenzheng Feng, Yuxiao Dong, Tinglin Huang, Ziqi Yin, Xu Cheng, Evgeny Kharlamov, Jie Tang:
GRAND+: Scalable Graph Random Neural Networks. CoRR abs/2203.06389 (2022) - 2021
- [c8]Tinglin Huang, Yuxiao Dong, Ming Ding, Zhen Yang, Wenzheng Feng, Xinyu Wang, Jie Tang:
MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems. KDD 2021: 665-674 - [c7]Xiang Wang, Tinglin Huang, Dingxian Wang, Yancheng Yuan, Zhenguang Liu, Xiangnan He, Tat-Seng Chua:
Learning Intents behind Interactions with Knowledge Graph for Recommendation. WWW 2021: 878-887 - [i1]Xiang Wang, Tinglin Huang, Dingxian Wang, Yancheng Yuan, Zhenguang Liu, Xiangnan He, Tat-Seng Chua:
Learning Intents behind Interactions with Knowledge Graph for Recommendation. CoRR abs/2102.07057 (2021)
2010 – 2019
- 2019
- [c6]Tinglin Huang, Yulin He, De-Xin Dai, Wenting Wang, Joshua Zhexue Huang:
Neural Network-Based Deep Encoding for Mixed-Attribute Data Classification. PAKDD (Workshops) 2019: 153-163 - 2018
- [c5]Yingying Zhu, Min Tong, Tinglin Huang, Zhenkun Wen, Qi Tian:
Learning Affective Features Based on VIP for Video Affective Content Analysis. PCM (3) 2018: 697-707
2000 – 2009
- 2009
- [c4]Jinsuo Lu, Tinglin Huang, Chunyan Wang:
Data Mining on Source Water Quality (Tianjin, China) for Forecasting Algae Bloom Based on Artificial Neural Network (ANN). CSIE (7) 2009: 191-195 - [c3]Hui Zhang, Tinglin Huang, Wenjie He:
Application of Heuristic Genetic Algorithm for Optimal Layout of Flow Measurement Stations in Water Distribution Networks. ICNC (4) 2009: 140-143 - [c2]Jinsuo Lu, Tinglin Huang:
Data Mining on Forecast Raw Water Quality from Online Monitoring Station Based on Decision-Making Tree. NCM 2009: 706-709 - 2008
- [c1]Jinsuo Lu, Tinglin Huang, Rui Hu:
Data Mining on Algae Concentrations (Chlorophyll) Time Series in Source Water Based on Wavelet. FSKD (5) 2008: 611-616
Coauthor Index
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