Deep Reinforcement Learning with Discrete Normalized Advantage Functions for Resource Management in Network Slicing

no code implementations • 10 Jun 2019 • Chen Qi, Yuxiu Hua, Rongpeng Li, Zhifeng Zhao, Honggang Zhang

Furthermore, as DPGD only works in continuous action space, we embed a k-nearest neighbor algorithm into DQL to quickly find a valid action in the discrete space nearest to the DPGD output.

Deep Reinforcement Learning Management +3

GAN-powered Deep Distributional Reinforcement Learning for Resource Management in Network Slicing

no code implementations • 10 May 2019 • Yuxiu Hua, Rongpeng Li, Zhifeng Zhao, Xianfu Chen, Honggang Zhang

Moreover, we further develop Dueling GAN-DDQN, which uses a specially designed dueling generator, to learn the action-value distribution by estimating the state-value distribution and the action advantage function.

Deep Reinforcement Learning Distributional Reinforcement Learning +4

Deep Learning with Long Short-Term Memory for Time Series Prediction

no code implementations • 24 Oct 2018 • Yuxiu Hua, Zhifeng Zhao, Rongpeng Li, Xianfu Chen, Zhiming Liu, Honggang Zhang

Time series prediction can be generalized as a process that extracts useful information from historical records and then determines future values.

Time Series Time Series Prediction

Traffic Prediction Based on Random Connectivity in Deep Learning with Long Short-Term Memory

no code implementations • 8 Nov 2017 • Yuxiu Hua, Zhifeng Zhao, Rongpeng Li, Xianfu Chen, Zhiming Liu, Honggang Zhang

So, the RCLSTM, with certain intrinsic sparsity, have many neural connections absent (distinguished from the full connectivity) and which leads to the reduction of the parameters to be trained and the computational cost.

Traffic Prediction