6 citations · 33 across the 11 of their papers we have counts for
11 papers
DynImp: Dynamic Imputation for Wearable Sensing Data Through Sensory and Temporal Relatedness
Zepeng Huo, Taowei Ji, Yifei Liang +4
In wearable sensing applications, data is inevitable to be irregularly sampled or partially missing, which pose challenges for any downstream application. An unique aspect of weara…
Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data
Zepeng Huo, Xiaoning Qian, Shuai Huang +2
Medical events of interest, such as mortality, often happen at a low rate in electronic medical records, as most admitted patients survive. Training models with this imbalance rate…
VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition
Randy Ardywibowo, Shahin Boluki, Zhangyang Wang +3
In many machine learning tasks, input features with varying degrees of predictive capability are acquired at varying costs. In order to optimize the performance-cost trade-off, one…
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery
Zepeng Huo, Arash PakBin, Xiaohan Chen +6
Activity recognition in wearable computing faces two key challenges: i) activity characteristics may be context-dependent and change under different contexts or situations; ii) unk…
UQ-CHI: An Uncertainty Quantification-Based Contemporaneous Health Index for Degenerative Disease Monitoring
Aven Samareh, Shuai Huang
Developing knowledge-driven contemporaneous health index (CHI) that can precisely reflect the underlying patient across the course of the condition's progression holds a unique val…
Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models
Randy Ardywibowo, Guang Zhao, Zhangyang Wang +3
Emerging wearable sensors have enabled the unprecedented ability to continuously monitor human activities for healthcare purposes. However, with so many ambient sensors collecting…
Safe Active Feature Selection for Sparse Learning
Shaogang Ren, Jianhua Z. Huang, Shuai Huang +1
We present safe active incremental feature selection~(SAIF) to scale up the computation of LASSO solutions. SAIF does not require a solution from a heavier penalty parameter as in…
A Robust AUC Maximization Framework with Simultaneous Outlier Detection and Feature Selection for Positive-Unlabeled Classification
Ke Ren, Haichuan Yang, Yu Zhao +4
The positive-unlabeled (PU) classification is a common scenario in real-world applications such as healthcare, text classification, and bioinformatics, in which we only observe a f…
Predicting Depression Severity by Multi-Modal Feature Engineering and Fusion
Aven Samareh, Yan Jin, Zhangyang Wang +2
We present our preliminary work to determine if patient's vocal acoustic, linguistic, and facial patterns could predict clinical ratings of depression severity, namely Patient Heal…
Robust Emotion Recognition from Low Quality and Low Bit Rate Video: A Deep Learning Approach
Bowen Cheng, Zhangyang Wang, Zhaobin Zhang +5
Emotion recognition from facial expressions is tremendously useful, especially when coupled with smart devices and wireless multimedia applications. However, the inadequate network…
Prognostics of Surgical Site Infections using Dynamic Health Data
Chuyang Ke, Yan Jin, Heather Evans +4
Surgical Site Infection (SSI) is a national priority in healthcare research. Much research attention has been attracted to develop better SSI risk prediction models. However, most…