Variance Reduced Stochastic Gradient Descent with Sufficient Decrease. - Fanhua Shang; Yuanyuan Liu 001; James Cheng; Kelvin Kai Wing Ng; Yuichi Yoshida (CoRR, 2017)

Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. - Fanhua Shang; Yuanyuan Liu 001; Kaiwen Zhou; James Cheng; Kelvin Kai Wing Ng; Yuichi Yoshida (AISTATS, 2018)

A General and Efficient Querying Method for Learning to Hash. - Jinfeng Li; Xiao Yan 002; Jie Zhang 046; An Xu; James Cheng; Jie Liu 048; Kelvin Kai Wing Ng; Ti-Chung Cheng (SIGMOD Conference, 2018)

Pyramid: A General Framework for Distributed Similarity Search on Large-scale Datasets. - Shiyuan Deng; Xiao Yan 002; Kelvin Kai Wing Ng; Chenyu Jiang; James Cheng (IEEE BigData, 2019)

Pyramid: A General Framework for Distributed Similarity Search. - Shiyuan Deng; Xiao Yan 002; Kelvin Kai Wing Ng; Chenyu Jiang; James Cheng (CoRR, 2019)

Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search. - Xinyan Dai; Xiao Yan 002; Kelvin Kai Wing Ng; Jie Liu 048; James Cheng (CoRR, 2019)

Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning. - Xinyan Dai; Xiao Yan 002; Kaiwen Zhou; Han Yang 002; Kelvin Kai Wing Ng; James Cheng; Yu Fan (CoRR, 2019)

Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search. - Xinyan Dai; Xiao Yan 002; Kelvin Kai Wing Ng; Jiu Liu; James Cheng (AAAI, 2020)