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 …
Symmetric nonnegative matrix factorization-based community detection models and their convergence analysis
Community detection is a popular yet thorny issue in social network analysis. A symmetric
and nonnegative matrix factorization (SNMF) model based on a nonnegative multiplicative …
and nonnegative matrix factorization (SNMF) model based on a nonnegative multiplicative …
Highly-accurate community detection via pointwise mutual information-incorporated symmetric non-negative matrix factorization
Community detection, aiming at determining correct affiliation of each node in a network, is a
critical task of complex network analysis. Owing to its high efficiency, Symmetric and Non …
critical task of complex network analysis. Owing to its high efficiency, Symmetric and Non …
Generalized nesterov's acceleration-incorporated, non-negative and adaptive latent factor analysis
A non-negative latent factor (NLF) model with a single latent factor-dependent, non-negative
and multiplicative update (SLF-NMU) algorithm is frequently adopted to extract useful …
and multiplicative update (SLF-NMU) algorithm is frequently adopted to extract useful …
[HTML][HTML] 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 dexterity of robotic operation, dexterous manipulation of
multi-fingered robotic hands with reinforcement learning is an interesting subject in robotics …
multi-fingered robotic hands with reinforcement learning is an interesting subject in robotics …
Symmetry and graph bi-regularized non-negative matrix factorization for precise community detection
Community is a fundamental and highly desired pattern in a Large-scale Undirected
Network (LUN). Community detection is a vital issue when LUN representation learning is …
Network (LUN). Community detection is a vital issue when LUN representation learning is …
An alternating-direction-method of multipliers-incorporated approach to symmetric non-negative latent factor analysis
Large-scale undirected weighted networks are frequently encountered in big-data-related
applications concerning interactions among a large unique set of entities. Such a network …
applications concerning interactions among a large unique set of entities. Such a network …
Solving complex-valued time-varying linear matrix equations via QR decomposition with applications to robotic motion tracking and on angle-of-arrival localization
VN Katsikis, SD Mourtas… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The problem of solving linear equations is considered as one of the fundamental problems
commonly encountered in science and engineering. In this article, the complex-valued time …
commonly encountered in science and engineering. In this article, the complex-valued time …
Neural module networks: a review
H Fashandi - Neurocomputing, 2023 - Elsevier
The capability of deep neural networks to automatically learn informative features from data
is their asset. For instance, a convolutional layer learns the filters based on their placement …
is their asset. For instance, a convolutional layer learns the filters based on their placement …
MNL: A highly-efficient model for large-scale dynamic weighted directed network representation
M Chen, C He, X Luo - IEEE Transactions on Big Data, 2022 - ieeexplore.ieee.org
A Non-negative Latent-factorization-of-tensors model relying on a N onnegative and M
ultiplicative U pdate on I ncomplete T ensors (NMU-IT) algorithm facilitates efficient …
ultiplicative U pdate on I ncomplete T ensors (NMU-IT) algorithm facilitates efficient …