An overview of data-driven battery health estimation technology for battery management system

M Chen, G Ma, W Liu, N Zeng, X Luo - Neurocomputing, 2023 - Elsevier
Battery degradation, caused by multiple coupled degradation mechanisms, severely affects
the safety and sustainability of a battery management system (BMS). The battery state of …

An overview of recommendation techniques and their applications in healthcare

W Yue, Z Wang, J Zhang, X Liu - IEEE/CAA Journal of …, 2021 - ieeexplore.ieee.org
With the increasing amount of information on the internet, recommendation system (RS) has
been utilized in a variety of fields as an efficient tool to overcome information overload. In …

A novel approach to large-scale dynamically weighted directed network representation

X Luo, H Wu, Z Wang, J Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A dynamically weighted directed network (DWDN) is frequently encountered in various big
data-related applications like a terminal interaction pattern analysis system (TIPAS) …

HRST-LR: a hessian regularization spatio-temporal low rank algorithm for traffic data imputation

X Xu, M Lin, X Luo, Z Xu - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
Intelligent Transportation Systems (ITSs) are vital for alleviating traffic congestion and
improving traffic efficiency. Due to the delay of network transmission and failure of detectors …

EDMF: Efficient deep matrix factorization with review feature learning for industrial recommender system

H Liu, C Zheng, D Li, X Shen, K Lin… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Recommendation accuracy is a fundamental problem in the quality of the recommendation
system. In this article, we propose an efficient deep matrix factorization (EDMF) with review …

Fast and accurate non-negative latent factor analysis of high-dimensional and sparse matrices in recommender systems

X Luo, Y Zhou, Z Liu, MC Zhou - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A fast non-negative latent factor (FNLF) model for a high-dimensional and sparse (HiDS)
matrix adopts a Single Latent Factor-dependent, Non-negative, Multiplicative and …

A generalized Nesterov's accelerated gradient-incorporated non-negative latent-factorization-of-tensors model for efficient representation to dynamic QoS data

M Chen, R Wang, Y Qiao, X Luo - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Dynamic Quality-of-Service (QoS) data can be efficiently represented by a Non-negative
Latent-factorization-of-tensors model, which relies on a Non-negative and Multiplicative …

Efficient and high-quality recommendations via momentum-incorporated parallel stochastic gradient descent-based learning

X Luo, W Qin, A Dong, K Sedraoui… - IEEE/CAA Journal of …, 2020 - ieeexplore.ieee.org
A recommender system (RS) relying on latent factor analysis usually adopts stochastic
gradient descent (SGD) as its learning algorithm. However, owing to its serial mechanism …

Proximal alternating-direction-method-of-multipliers-incorporated nonnegative latent factor analysis

F Bi, X Luo, B Shen, H Dong… - IEEE/CAA Journal of …, 2023 - ieeexplore.ieee.org
High-dimensional and incomplete (HDI) data subject to the nonnegativity constraints are
commonly encountered in a big data-related application concerning the interactions among …

A fast nonnegative autoencoder-based approach to latent feature analysis on high-dimensional and incomplete data

F Bi, T He, X Luo - IEEE Transactions on Services Computing, 2023 - ieeexplore.ieee.org
High-Dimensional and Incomplete (HDI) data are frequently encountered in various Big
Data-related applications. Despite its incompleteness, an HDI data repository contains rich …