no code implementations • 28 Feb 2023 • Shenzheng Zhang, Qi Tan, Xinzhi Zheng, Yi Ren, Xu Zhao
The gap between the randomly initialized item ID embedding and the well-trained warm item ID embedding makes the cold items hard to suit the recommendation system, which is trained on the data of historical warm items.
no code implementations • 14 Sep 2020 • Qi Tan, Yang Liu, Jiming Liu
Deep learning has achieved incredible success over the past years, especially in various challenging predictive spatio-temporal analytics (PSTA) tasks, such as disease prediction, climate forecast, and traffic prediction, where intrinsic dependency relationships among data exist and generally manifest at multiple spatio-temporal scales.
no code implementations • ICLR 2019 • Qi Tan, Pingzhong Tang, Ke Xu, Weiran Shen, Song Zuo
Generative neural networks map a standard, possibly distribution to a complex high-dimensional distribution, which represents the real world data set.