Fast and accurate non-negative latent factor analysis of high-dimensional and sparse matrices in recommender systems
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 …
matrix adopts a Single Latent Factor-dependent, Non-negative, Multiplicative and …
Techno-economic and environmental benefits-oriented human–robot collaborative disassembly line balancing optimization in remanufacturing
The remanufacturing process, driven by human–robot collaboration technology, is becoming
an important carrier for the circular economy, contributing to economic development while …
an important carrier for the circular economy, contributing to economic development while …
A momentum-accelerated Hessian-vector-based latent factor analysis model
Service-oriented applications commonly involve high-dimensional and sparse (HiDS)
interactions among users and service-related entities, eg, user-item interactions from a …
interactions among users and service-related entities, eg, user-item interactions from a …
Optimal layout planning for human robot collaborative assembly systems and visualization through immersive technologies
The deployment of Industry 4.0 emerging technologies such as Augmented reality (AR),
Virtual reality (VR), and collaborative Robots enhances flexibility and precision in the …
Virtual reality (VR), and collaborative Robots enhances flexibility and precision in the …
Predicting protein-protein interactions using sequence and network information via variational graph autoencoder
Protein-protein interactions (PPIs) play a critical role in the proteomics study, and a variety of
computational algorithms have been developed to predict PPIs. Though effective, their …
computational algorithms have been developed to predict PPIs. Though effective, their …
Gradient-feedback ZNN for unconstrained time-variant convex optimization and robot manipulator application
Z Fu, Y Zhang, N Tan - IEEE Transactions on Industrial …, 2023 - ieeexplore.ieee.org
Optimization problems are frequently encountered in various fields. In this article, the
unconstrained time-variant convex optimization (UTVCO) problem is investigated. Generally …
unconstrained time-variant convex optimization (UTVCO) problem is investigated. Generally …
A Generalized Nesterov-Accelerated Second-Order Latent Factor Model for High-Dimensional and Incomplete Data
W Li, R Wang, X Luo - IEEE Transactions on Neural Networks …, 2023 - ieeexplore.ieee.org
High-dimensional and incomplete (HDI) data are frequently encountered in big date-related
applications for describing restricted observed interactions among large node sets. How to …
applications for describing restricted observed interactions among large node sets. How to …
BO-SMOTE: A Novel Bayesian-Optimization-Based Synthetic Minority Oversampling Technique
S Yan, Z Zhao, S Liu, MC Zhou - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
An oversampling technique balances a dataset by increasing the number of minority
samples. It is a common and effective method in imbalanced learning. However, most …
samples. It is a common and effective method in imbalanced learning. However, most …
Data-driven industrial robot arm calibration: a machine learning perspective
Robot arms have been widely used in industry. The absolute positioning error of robots
without calibration can reach several millimeters, which cannot meet the application …
without calibration can reach several millimeters, which cannot meet the application …
Lara: A light and anti-overfitting retraining approach for unsupervised anomaly detection
Most of current anomaly detection models assume that the normal pattern remains same all
the time. However, the normal patterns of Web services change dramatically and frequently …
the time. However, the normal patterns of Web services change dramatically and frequently …