77 citations · 169 across the 7 of their papers we have counts for
7 papers
Probably Approximate Shapley Fairness with Applications in Machine Learning
Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim +2
The Shapley value (SV) is adopted in various scenarios in machine learning (ML), including data valuation, agent valuation, and feature attribution, as it satisfies their fairness…
Data-driven discoveries of Bäcklund transforms and soliton evolution equations via deep neural network learning schemes
Zijian Zhou, Li Wang, Weifang Weng +1
We introduce a deep neural network learning scheme to learn the Bäcklund transforms (BTs) of soliton evolution equations and an enhanced deep learning scheme for data-driven solito…
Aggressive Q-Learning with Ensembles: Achieving Both High Sample Efficiency and High Asymptotic Performance
Yanqiu Wu, Xinyue Chen, Che Wang +2
Recent advances in model-free deep reinforcement learning (DRL) show that simple model-free methods can be highly effective in challenging high-dimensional continuous control tasks…
Randomized Ensembled Double Q-Learning: Learning Fast Without a Model
Xinyue Chen, Che Wang, Zijian Zhou +1
Using a high Update-To-Data (UTD) ratio, model-based methods have recently achieved much higher sample efficiency than previous model-free methods for continuous-action DRL benchma…
Solving forward and inverse problems of the logarithmic nonlinear Schrodinger equation with PT-symmetric harmonic potential via deep learning
Zijian Zhou, Zhenya Yan
In this paper, we investigate the logarithmic nonlinear Schrödinger (LNLS) equation with the parity-time (PT)-symmetric harmonic potential, which is an important physical model in…
Gaussian Vector: An Efficient Solution for Facial Landmark Detection
Yilin Xiong, Zijian Zhou, Yuhao Dou +1
Significant progress has been made in facial landmark detection with the development of Convolutional Neural Networks. The widely-used algorithms can be classified into coordinate…
BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement Learning
Xinyue Chen, Zijian Zhou, Zheng Wang +3
There has recently been a surge in research in batch Deep Reinforcement Learning (DRL), which aims for learning a high-performing policy from a given dataset without additional int…