An algorithm for efficient privacy-preserving item-based collaborative filtering D Li, C Chen, Q Lv, L Shang, Y Zhao, T Lu, N Gu Future Generation Computer Systems 55, 311-320, 2016 | 134 | 2016 |
WEMAREC: Accurate and scalable recommendation through weighted and ensemble matrix approximation C Chen, D Li, Y Zhao, Q Lv, L Shang Proceedings of the international ACM SIGIR conference on research and …, 2015 | 57 | 2015 |
Low-rank matrix approximation with stability D Li, C Chen, Q Lv, J Yan, L Shang, S Chu Proceedings of the International Conference on Machine Learning 951, 295-303, 2016 | 52 | 2016 |
Unsupervised detection of contextual anomaly in remotely sensed data Q Liu, R Klucik, C Chen, G Grant, D Gallaher, Q Lv, L Shang Remote Sensing of Environment 202, 75-87, 2017 | 51 | 2017 |
Resistance training using prior bias: toward unbiased scene graph generation C Chen, Y Zhan, B Yu, L Liu, Y Luo, B Du Proceedings of the AAAI Conference on Artificial Intelligence 36 (1), 212-220, 2022 | 44 | 2022 |
Mixture-rank matrix approximation for collaborative filtering D Li, C Chen, W Liu, T Lu, N Gu, S Chu Advances in Neural Information Processing Systems 30, 2017 | 42 | 2017 |
AdaError: An Adaptive Learning Rate Method for Matrix Approximation-based Collaborative Filtering D Li, C Chen, Q Lv, H Gu, T Lu, L Shang, N Gu, SM Chu International World Wide Web Conference, WWW, 2018 | 37 | 2018 |
MPMA: Mixture Probabilistic Matrix Approximation for Collaborative Filtering C Chen, D Li, Q Lv, J Yan, SM Chu, L Shang Proceedings of the International Joint Conference on Artificial Intelligence …, 2016 | 33 | 2016 |
GLOMA: Embedding Global Information in Local Matrix Approximation Models for Collaborative Filtering C Chen, D Li, Q Lv, J Yan, L Shang, SM Chu Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2017 …, 2017 | 24 | 2017 |
Modeling dynamic user preference via dictionary learning for sequential recommendation C Chen, D Li, J Yan, X Yang IEEE Transactions on Knowledge and Data Engineering 34 (11), 5446-5458, 2022 | 20 | 2022 |
Scalable and Explainable 1-Bit Matrix Completion via Graph Signal Learning C Chen, D Li, J Yan, H Huang, X Yang Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-21), 2021 | 15 | 2021 |
ERMMA: Expected Risk Minimization for Matrix Approximation-based Recommender Systems D Li, C Chen, Q Lv, L Shang, SM Chu, H Zha Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2017), 2017 | 15 | 2017 |
Learning self-modulating attention in continuous time space with applications to sequential recommendation C Chen, H Geng, N Yang, J Yan, D Xue, J Yu, X Yang Proceedings of the International Conference on Machine Learning, 1606-1616, 2021 | 14 | 2021 |
Mixture matrix approximation for collaborative filtering D Li, C Chen, T Lu, SM Chu, N Gu IEEE Transactions on Knowledge and Data Engineering 33 (6), 2640-2653, 2021 | 13 | 2021 |
Collaborative Filtering with Noisy Ratings L Dongsheng, C Chen, Z Gong, T Lu, SM Chu, N Gu Proceedings of the International Conference on Data Mining, pp. 747-755, 2019 | 12* | 2019 |
Pyramid Graph Neural Network: a Graph Sampling and Filtering Approach for Multi-scale Disentangled Representations H Geng, C Chen, Y He, G Zeng, Z Han, H Chai, J Yan Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data …, 2023 | 8 | 2023 |
NeuSE: A neural snapshot ensemble method for collaborative filtering D Li, H Liu, C Chen, Y Zhao, SM Chu, B Yang ACM Transactions on Knowledge Discovery from Data (TKDD) 15 (6), 1-20, 2021 | 5 | 2021 |
EasyDGL: Encode, Train and Interpret for Continuous-Time Dynamic Graph Learning C Chen, H Geng, N Yang, X Yang, J Yan IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 4 | 2024 |
Graph Signal Sampling for Inductive One-Bit Matrix Completion: a Closed-form Solution C Chen, H Geng, G Zeng, Z Han, H Chai, X Yang, J Yan Proceedings of the International Conference on Learning Representations, 2023 | 4 | 2023 |