Collapsing bandits and their application to public health intervention

A Mate, J Killian, H Xu, A Perrault… - Advances in Neural …, 2020 - proceedings.neurips.cc
We propose and study Collapsing Bandits, a new restless multi-armed bandit (RMAB)
setting in which each arm follows a binary-state Markovian process with a special structure …

Physics-constrained deep learning for robust inverse ecg modeling

J Xie, B Yao - IEEE Transactions on Automation Science and …, 2022 - ieeexplore.ieee.org
The rapid development in advanced sensing and imaging brings about a data-rich
environment, facilitating the effective modeling, monitoring, and control of complex systems …

An Industrial Multi Agent System for real-time distributed collaborative prognostics

AS Palau, MH Dhada, K Bakliwal… - Engineering Applications of …, 2019 - Elsevier
Despite increasing interest, real-time prognostics (failure prediction) is still not widespread in
industry due to the difficulties of existing systems to adapt to the dynamic and …

Constrained markov decision process modeling for optimal sensing of cardiac events in mobile health

B Yao, Y Chen, H Yang - IEEE Transactions on Automation …, 2021 - ieeexplore.ieee.org
Rapid advances in the smartphone, wearable sensing, and wireless communication provide
an unprecedented opportunity to develop mobile systems for smart health management …

Spatiotemporal regularization for inverse ECG modeling

B Yao, H Yang - IISE Transactions on Healthcare Systems …, 2020 - Taylor & Francis
Advanced sensing such as the wearable sensor network provides an unprecedented
opportunity to capture a wealth of information pertinent to space-time electrical activity of the …

Machine learning discovery of longitudinal patterns of depression and suicidal ideation

J Gong, GE Simon, S Liu - PloS one, 2019 - journals.plos.org
Background and aim Depression is often accompanied by thoughts of self-harm, which are a
strong predictor of subsequent suicide attempt and suicide death. Few empirical data are …

An online updating method for time-varying preference learning

X Zhu, J Feng, S Huang, C Chen - Transportation Research Part C …, 2020 - Elsevier
The rapid proliferation of smart, personal technologies has given birth to smart
Transportation Demand Management (TDM) systems that can give personalized incentives …

Comparison of agent deployment strategies for collaborative prognosis

M Dhada, MP Hernández, AS Palau… - … on prognostics and …, 2021 - ieeexplore.ieee.org
Collaborative prognosis is a technique that enables the industrial assets to learn from similar
other assets in a fleet, and improve their data-driven prognosis models. When collaborative …

Secure and communications‐efficient collaborative prognosis

M Dhada, AK Jain, M Herrera… - IET Collaborative …, 2020 - Wiley Online Library
Collaborative prognosis is a technique that is used to enable assets to improve their ability
to predict failures by learning from the failures of similar other assets. This is typically made …

A learning framework for personalized random utility maximization (rum) modeling of user behavior

J Feng, X Zhu, F Wang, S Huang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Understanding user behavior is crucial for the success of many emerging applications that
aim to provide personalized services for target users, such as many patient-centered health …