no code implementations • 22 Jul 2022 • Zhaoyue Xia, Jun Du, Yong Ren
Compared with perfect data, quantization poses fundamental challenges on loss of data accuracy, which further impacts the convergence of the algorithms.
no code implementations • 1 Feb 2022 • Wei Wei, Jingjing Wang, Jun Du, Zhengru Fang, Chunxiao Jiang, Yong Ren
Simulations show that underwater disturbances have a large impact on the system considering communication delay.
no code implementations • 26 Sep 2021 • Jun Du, Chunxiao Jiang, Abderrahim Benslimane, Song Guo, Yong Ren
Based on this dynamic access model, a Stackelberg differential game based cloud computing resource sharing mechanism is proposed to facilitate the resource trading between the cloud computing service provider (CCP) and different edge computing service providers (ECPs).
no code implementations • 24 Jan 2019 • Jingjing Wang, Chunxiao Jiang, Haijun Zhang, Yong Ren, Kwang-cheng Chen, Lajos Hanzo
Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services.
1 code implementation • CVPR 2018 • Yucen Luo, Jun Zhu, Mengxi Li, Yong Ren, Bo Zhang
In SNTG, a graph is constructed based on the predictions of the teacher model, i. e., the implicit self-ensemble of models.
no code implementations • NeurIPS 2016 • Yang Song, Jun Zhu, Yong Ren
We propose a vector-valued regression problem whose solution is equivalent to the reproducing kernel Hilbert space (RKHS) embedding of the Bayesian posterior distribution.
no code implementations • NeurIPS 2016 • Yong Ren, Jialian Li, Yucen Luo, Jun Zhu
Maximum mean discrepancy (MMD) has been successfully applied to learn deep generative models for characterizing a joint distribution of variables via kernel mean embedding.
no code implementations • 19 Feb 2016 • Yong Ren, Yining Wang, Jun Zhu
Spectral methods have been applied to learn unsupervised topic models, such as latent Dirichlet allocation (LDA), with provable guarantees.