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Xinyan Dai
Xinyan Dai
Ph.D candidate at the Chinese University of Hong Kong.
Verified email at cse.cuhk.edu.hk - Homepage
Title
Cited by
Cited by
Year
Norm-ranging lsh for maximum inner product search
X Yan, J Li, X Dai, H Chen, J Cheng
Advances in Neural Information Processing Systems 31, 2018
602018
Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning
X Dai, X Yan, K Zhou, H Yang, KKW Ng, J Cheng, Y Fan
arXiv preprint arXiv:1911.04655, 2019
492019
Self-enhanced gnn: Improving graph neural networks using model outputs
H Yang, X Yan, X Dai, Y Chen, J Cheng
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
352021
Understanding and Improving Proximity Graph Based Maximum Inner Product Search
J Liu, X Yan, X Dai, Z Li, J Cheng, MC Yang
Proceedings of the AAAI Conference on Artificial Intelligence 34 (01), 139-146, 2020
292020
Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search
X Dai, X Yan, KKW Ng, J Liu, J Cheng
Proceedings of the AAAI Conference on Artificial Intelligence 34 (01), 51-58, 2020
282020
Convolutional Embedding for Edit Distance
X Dai, X Yan, K Zhou, Y Wang, H Yang, J Cheng
Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020
24*2020
Pmd: An optimal transportation-based user distance for recommender systems
Y Meng, X Dai, X Yan, J Cheng, W Liu, J Guo, B Liao, G Chen
Advances in Information Retrieval: 42nd European Conference on IR Research …, 2020
8*2020
Norm-Range Partition: A Universal Catalyst for LSH based Maximum Inner Product Search (MIPS)
X Yan, X Dai, J Liu, K Zhou, J Cheng
arXiv preprint arXiv:1810.09104, 2018
12018
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