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
arXiv preprint arXiv:1809.08782, 2018
282018
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
112019
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
62020
Self-enhanced gnn: Improving graph neural networks using model outputs
H Yang, X Yan, X Dai, Y Chen, J Cheng
arXiv preprint arXiv:2002.07518, 2020
62020
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
52020
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
4*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 12036, 272, 2020
22020
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
2018
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