Yu Zheng

TL;DR: A secure cross-regional machine learning system that allows a learning process to be jointly trained over different regions’ clients with the same user samples but different attribute sets, processing the data stored in each of them without exchanging their raw data.

TL;DR: This paper designs a novel search space tailored for ST-domain which consists of two categories of components: optional convolution operations at each layer to automatically extract multi-range spatio-temporal dependencies and learnable skip connections among layers to dynamically fuse low- and high-level ST-features.

TL;DR: The food delivery task grouping problem is studied so as to improve food delivery efficiency and alleviate the pain of waiting for users, and an effective task grouping method is proposed consisting of a greedy algorithm and a replacement algorithm is proposed.

TL;DR: Real-time system on the cloud providing citywide traffic speed and volume information and fine-grained pollutant emission of vehicles in Guiyang city, and the experimental results consistently demonstrate the advantages of the proposed neural memorization and generalization approach.