Q
Qiang Yang
Researcher at Hong Kong University of Science and Technology
Publications - 1795
Citations - 96705
Qiang Yang is an academic researcher from Hong Kong University of Science and Technology. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 112, co-authored 1117 publications receiving 71540 citations. Previous affiliations of Qiang Yang include University of London & Zhejiang University of Technology.
Papers
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Journal ArticleDOI
Secure Federated Matrix Factorization
TL;DR: In this article, the authors proposed a secure matrix factorization framework under the federated learning setting, called FedMF, where each user only uploads the gradient information (instead of the raw preference data) to the server.
Proceedings ArticleDOI
Adaptive Temporal Radio Maps for Indoor Location Estimation
Jie Yin,Qiang Yang,Lionel M. Ni +2 more
TL;DR: A novel method to adapt the temporal radio maps for indoor location estimation by offsetting the variational environmental factors using data mining techniques and reference points and can effectively accommodate the variations of signal-strength values over different time periods without the need to rebuild the radio maps repeatedly.
Journal ArticleDOI
Towards mobile intelligence: Learning from GPS history data for collaborative recommendation
TL;DR: A mobile recommendation system to answer popular location-related queries in daily life, and proposes three algorithms based on collaborative filtering which can consistently outperform the competing baselines and the newly proposed third algorithm can also outperform the authors' other two previous algorithms.
Journal ArticleDOI
A Level-Based Learning Swarm Optimizer for Large-Scale Optimization
TL;DR: This work considers particles in the swarm as mixed-level students and proposes a level-based learning swarm optimizer (LLSO) to settle large-scale optimization, which is still considerably challenging in evolutionary computation.
Journal ArticleDOI
Effective and efficient dimensionality reduction for large-scale and streaming data preprocessing
Jun Yan,Benyu Zhang,Ning Liu,Shuicheng Yan,Qiansheng Cheng,Weiguo Fan,Qiang Yang,Wensi Xi,Zheng Chen +8 more
TL;DR: An overview of the popularly used feature extraction and selection algorithms under a unified framework is given and two novel dimensionality reduction algorithms based on the orthogonal centroid algorithm (OC) are proposed.