On layer normalization in the transformer architecture R Xiong, Y Yang, D He, K Zheng, S Zheng, C Xing, H Zhang, Y Lan, ... International Conference on Machine Learning, 10524-10533, 2020 | 1024 | 2020 |
Efficient private ERM for smooth objectives J Zhang, K Zheng, W Mou, L Wang arXiv preprint arXiv:1703.09947, 2017 | 156 | 2017 |
Generalization bounds of sgld for non-convex learning: Two theoretical viewpoints W Mou, L Wang, X Zhai, K Zheng Conference on Learning Theory, 605-638, 2018 | 152 | 2018 |
Locally differentially private (contextual) bandits learning K Zheng, T Cai, W Huang, Z Li, L Wang Advances in Neural Information Processing Systems 33, 12300-12310, 2020 | 61 | 2020 |
Efficient online portfolio with logarithmic regret H Luo, CY Wei, K Zheng Advances in neural information processing systems 31, 2018 | 60 | 2018 |
Collect at once, use effectively: Making non-interactive locally private learning possible K Zheng, W Mou, L Wang International Conference on Machine Learning, 4130-4139, 2017 | 50 | 2017 |
Multi-behavior self-supervised learning for recommendation J Xu, C Wang, C Wu, Y Song, K Zheng, X Wang, C Wang, G Zhou, K Gai Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023 | 23 | 2023 |
Combinatorial semi-bandit in the non-stationary environment W Chen, L Wang, H Zhao, K Zheng Uncertainty in Artificial Intelligence, 865-875, 2021 | 22 | 2021 |
Graph contrastive learning with generative adversarial network C Wu, C Wang, J Xu, Z Liu, K Zheng, X Wang, Y Song, K Gai Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 19 | 2023 |
Equipping experts/bandits with long-term memory K Zheng, H Luo, I Diakonikolas, L Wang Advances in Neural Information Processing Systems 32, 2019 | 19 | 2019 |
Instant Representation Learning for Recommendation over Large Dynamic Graphs C Wu, C Wang, J Xu, Z Fang, T Gu, C Wang, Y Song, K Zheng, X Wang, ... 2023 IEEE 39th International Conference on Data Engineering (ICDE), 82-95, 2023 | 6 | 2023 |
(Locally) differentially private combinatorial semi-bandits X Chen, K Zheng, Z Zhou, Y Yang, W Chen, L Wang International Conference on Machine Learning, 1757-1767, 2020 | 4 | 2020 |
Twin v2: Scaling ultra-long user behavior sequence modeling for enhanced ctr prediction at kuaishou Z Si, L Guan, ZX Sun, X Zang, J Lu, Y Hui, X Cao, Z Yang, Y Zheng, ... Proceedings of the 33rd ACM International Conference on Information and …, 2024 | 3 | 2024 |
DimeRec: A Unified Framework for Enhanced Sequential Recommendation via Generative Diffusion Models W Li, R Huang, H Zhao, C Liu, K Zheng, Q Liu, N Mou, G Zhou, D Lian, ... arXiv preprint arXiv:2408.12153, 2024 | 3 | 2024 |
Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems K Zheng, H Zhao, R Huang, B Zhang, N Mou, Y Niu, Y Song, H Wang, ... Proceedings of the ACM on Web Conference 2024, 3621-3631, 2024 | 3 | 2024 |
Large Language Models Enhanced Collaborative Filtering Z Sun, Z Si, X Zang, K Zheng, Y Song, X Zhang, J Xu Proceedings of the 33rd ACM International Conference on Information and …, 2024 | 2 | 2024 |
PANE-GNN: Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation Z Liu, C Wang, J Xu, C Wu, K Zheng, Y Song, N Mou, K Gai arXiv preprint arXiv:2306.04095, 2023 | 2 | 2023 |
Incorporating dynamic temperature estimation into contrastive learning on graphs Z Liu, C Wang, L Yang, Y Lou, H Feng, C Wu, K Zheng, Y Song 2024 IEEE 40th International Conference on Data Engineering (ICDE), 2889-2903, 2024 | 1 | 2024 |
RecFlow: An Industrial Full Flow Recommendation Dataset Q Liu, K Zheng, R Huang, W Li, K Cai, Y Chai, Y Niu, Y Hui, B Han, N Mou, ... arXiv preprint arXiv:2410.20868, 2024 | | 2024 |
UniSAR: Modeling User Transition Behaviors between Search and Recommendation T Shi, Z Si, J Xu, X Zhang, X Zang, K Zheng, D Leng, Y Niu, Y Song Proceedings of the 47th International ACM SIGIR Conference on Research and …, 2024 | | 2024 |