no code implementations • 26 Jan 2023 • Chenyu Li, Xia Jiang
We compared the traditional data augmentation evaluation methods with our proposed cross-validation evaluation framework Results Using traditional data augmentation evaluation meta hods will give a false impression of improving the performance.
no code implementations • 7 Oct 2022 • Chuhan Xu, Xia Jiang
Method: the iMedBot is a web application that we developed using the python Flask web framework and deployed on Amazon Web Services.
no code implementations • 3 Aug 2022 • Chuhan Xu, Pablo Coen-Pirani, Xia Jiang
We also find some interesting interacting pairs of hyperparameters such as learning rate and momentum, learning rate and decay, and batch size and epochs.
no code implementations • 24 Jun 2022 • Xia Jiang, Jian Zhang, Dan Li
This paper proposes an eco-driving framework for electric connected vehicles (CVs) based on reinforcement learning (RL) to improve vehicle energy efficiency at signalized intersections.
no code implementations • 24 Jun 2022 • Xia Jiang, Jian Zhang, Xiaoyu Shi, Jian Cheng
Meanwhile, the simulation results demonstrate the effectiveness of the delay reward, which is designed to outperform distributed reward mechanism} Compared with normal car-following behavior, the sensitivity analysis reveals that the energy can be saved to different extends (39. 27%-82. 51%) by adjusting the relative importance of the optimization goal.
no code implementations • 6 Nov 2021 • Xia Jiang, Xianlin Zeng, Jian Sun, Jie Chen, Lihua Xie
We prove that local variable estimates generated by the proposed algorithm achieve consensus and are attracted to a neighborhood of the optimal solution in expectation with an $\mathcal{O}(\frac{1}{T}+\frac{1}{\sqrt{T}})$ convergence rate, where $T$ is the total number of iterations.