Towards long lifetime battery: AI-based manufacturing and management

K Liu, Z Wei, C Zhang, Y Shang… - IEEE/CAA Journal of …, 2022 - ieeexplore.ieee.org
Technologies that accelerate the delivery of reliable battery-based energy storage will not
only contribute to decarbonization such as transportation electrification, smart grid, but also …

Dexterous manipulation for multi-fingered robotic hands with reinforcement learning: A review

C Yu, P Wang - Frontiers in Neurorobotics, 2022 - frontiersin.org
With the increasing demand for the dexterity of robotic operation, dexterous manipulation of
multi-fingered robotic hands with reinforcement learning is an interesting subject in the field …

A prediction-sampling-based multilayer-structured latent factor model for accurate representation to high-dimensional and sparse data

D Wu, X Luo, Y He, M Zhou - IEEE transactions on neural …, 2022 - ieeexplore.ieee.org
Performing highly accurate representation learning on a high-dimensional and sparse
(HiDS) matrix is of great significance in a big data-related application such as a …

Deconv-transformer (DecT): A histopathological image classification model for breast cancer based on color deconvolution and transformer architecture

Z He, M Lin, Z Xu, Z Yao, H Chen, A Alhudhaif… - Information …, 2022 - Elsevier
Histopathological image recognition of breast cancer is an onerous task. Although many
deep learning models have achieved good classification results on histopathological image …

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 latent factor analysis-based approach to online sparse streaming feature selection

D Wu, Y He, X Luo, MC Zhou - IEEE Transactions on Systems …, 2021 - ieeexplore.ieee.org
Online streaming feature selection (OSFS) has attracted extensive attention during the past
decades. Current approaches commonly assume that the feature space of fixed data …

A double-space and double-norm ensembled latent factor model for highly accurate web service QoS prediction

D Wu, P Zhang, Y He, X Luo - IEEE Transactions on Services …, 2022 - ieeexplore.ieee.org
Quality-of-Service (QoS), which describes the non-functional characteristics of Web service,
is of great significance in service selection. Since users cannot invoke all services to obtain …

An L1-and-L2-Norm-Oriented Latent Factor Model for Recommender Systems

D Wu, M Shang, X Luo, Z Wang - IEEE Transactions on Neural …, 2021 - ieeexplore.ieee.org
A recommender system (RS) is highly efficient in filtering people's desired information from
high-dimensional and sparse (HiDS) data. To date, a latent factor (LF)-based approach …

Two-stream graph convolutional network-incorporated latent feature analysis

F Bi, T He, Y **e, X Luo - IEEE Transactions on Services …, 2023 - ieeexplore.ieee.org
Historical Quality-of-Service (QoS) data describing existing user-service invocations are vital
to understanding user behaviors and cloud service conditions. Collaborative Filtering (CF) …

A fuzzy PID-incorporated stochastic gradient descent algorithm for fast and accurate latent factor analysis

Y Yuan, J Li, X Luo - IEEE Transactions on Fuzzy Systems, 2024 - ieeexplore.ieee.org
A stochastic gradient descent (SGD) based latent factor analysis (LFA) model can obtain
superior performance when performing representation to a high-dimensional and …