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ORCIDKelvin Kai Wing Ng
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2020 – today
- 2020
[c4]Xinyan Dai, Xiao Yan, Kelvin Kai Wing Ng, Jiu Liu, James Cheng:
Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search. AAAI 2020: 51-58
2010 – 2019
- 2019
- [c3]Shiyuan Deng, Xiao Yan, Kelvin Kai Wing Ng, Chenyu Jiang, James Cheng:
Pyramid: A General Framework for Distributed Similarity Search on Large-scale Datasets. IEEE BigData 2019: 1066-1071 - [i5]Shiyuan Deng, Xiao Yan, Kelvin Kai Wing Ng, Chenyu Jiang, James Cheng:
Pyramid: A General Framework for Distributed Similarity Search. CoRR abs/1906.10602 (2019) - [i4]Xinyan Dai, Xiao Yan, Kelvin Kai Wing Ng, Jie Liu, James Cheng:
Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search. CoRR abs/1911.04654 (2019) - [i3]Xinyan Dai, Xiao Yan, Kaiwen Zhou, Han Yang, Kelvin Kai Wing Ng, James Cheng, Yu Fan:
Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning. CoRR abs/1911.04655 (2019) - 2018
- [c2]Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida:
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. AISTATS 2018: 1027-1036 - [c1]Jinfeng Li, Xiao Yan, Jie Zhang, An Xu, James Cheng, Jie Liu
, Kelvin Kai Wing Ng, Ti-Chung Cheng:
A General and Efficient Querying Method for Learning to Hash. SIGMOD Conference 2018: 1333-1347 - [i2]Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida:
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. CoRR abs/1802.09933 (2018) - 2017
- [i1]Fanhua Shang, Yuanyuan Liu, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida:
Variance Reduced Stochastic Gradient Descent with Sufficient Decrease. CoRR abs/1703.06807 (2017)
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