279 citations · 559 across the 12 of their papers we have counts for
12 papers
Robust Actor-Critic Contextual Bandit for Mobile Health (mHealth) Interventions
Feiyun Zhu, Jun Guo, Ruoyu Li +1
We consider the actor-critic contextual bandit for the mobile health (mHealth) intervention. State-of-the-art decision-making algorithms generally ignore the outliers in the datase…
Adaptive Graph Convolutional Neural Networks
Ruoyu Li, Sheng Wang, Feiyun Zhu +1
Graph Convolutional Neural Networks (Graph CNNs) are generalizations of classical CNNs to handle graph data such as molecular data, point could and social networks. Current filters…
Robust Contextual Bandit via the Capped- norm
Feiyun Zhu, Xinliang Zhu, Sheng Wang +2
This paper considers the actor-critic contextual bandit for the mobile health (mHealth) intervention. The state-of-the-art decision-making methods in mHealth generally assume that…
Group-driven Reinforcement Learning for Personalized mHealth Intervention
Feiyun Zhu, Jun Guo, Zheng Xu +2
Due to the popularity of smartphones and wearable devices nowadays, mobile health (mHealth) technologies are promising to bring positive and wide impacts on people's health. State-…
Hyperspectral Unmixing: Ground Truth Labeling, Datasets, Benchmark Performances and Survey
Feiyun Zhu
Hyperspectral unmixing (HU) is a very useful and increasingly popular preprocessing step for a wide range of hyperspectral applications. However, the HU research has been constrain…
Effective Warm Start for the Online Actor-Critic Reinforcement Learning based mHealth Intervention
Feiyun Zhu, Peng Liao
Online reinforcement learning (RL) is increasingly popular for the personalized mobile health (mHealth) intervention. It is able to personalize the type and dose of interventions a…
Cohesion-based Online Actor-Critic Reinforcement Learning for mHealth Intervention
Feiyun Zhu, Peng Liao, Xinliang Zhu +2
In the wake of the vast population of smart device users worldwide, mobile health (mHealth) technologies are hopeful to generate positive and wide influence on people's health. The…
Accurate Urban Road Centerline Extraction from VHR Imagery via Multiscale Segmentation and Tensor Voting
Guangliang Cheng, Feiyun Zhu, Shiming Xiang +1
It is very useful and increasingly popular to extract accurate road centerlines from very-high-resolution (VHR) re- mote sensing imagery for various applications, such as road map…
10,000+ Times Accelerated Robust Subset Selection (ARSS)
Feiyun Zhu, Bin Fan, Xinliang Zhu +3
Subset selection from massive data with noised information is increasingly popular for various applications. This problem is still highly challenging as current methods are general…
Effective Spectral Unmixing via Robust Representation and Learning-based Sparsity
Feiyun Zhu, Ying Wang, Bin Fan +2
Hyperspectral unmixing (HU) plays a fundamental role in a wide range of hyperspectral applications. It is still challenging due to the common presence of outlier channels and the l…
Spectral Unmixing via Data-guided Sparsity
Feiyun Zhu, Ying Wang, Bin Fan +3
Hyperspectral unmixing, the process of estimating a common set of spectral bases and their corresponding composite percentages at each pixel, is an important task for hyperspectral…
Robust Hyperspectral Unmixing with Correntropy based Metric
Ying Wang, Chunhong Pan, Shiming Xiang +1
Hyperspectral unmixing is one of the crucial steps for many hyperspectral applications. The problem of hyperspectral unmixing has proven to be a difficult task in unsupervised work…