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 …
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 …
A nonnegative latent factor model for large-scale sparse matrices in recommender systems via alternating direction method
Nonnegative matrix factorization (NMF)-based models possess fine representativeness of a
target matrix, which is critically important in collaborative filtering (CF)-based recommender …
target matrix, which is critically important in collaborative filtering (CF)-based recommender …
A fast non-negative latent factor model based on generalized momentum method
Non-negative latent factor (NLF) models can efficiently acquire useful knowledge from high-
dimensional and sparse (HiDS) matrices filled with non-negative data. Single latent factor …
dimensional and sparse (HiDS) matrices filled with non-negative data. Single latent factor …
Algorithms of unconstrained non-negative latent factor analysis for recommender systems
Non-negativity is vital for a latent factor (LF)-based model to preserve the important feature
of a high-dimensional and sparse (HiDS) matrix in recommender systems, ie, none of its …
of a high-dimensional and sparse (HiDS) matrix in recommender systems, ie, none of its …
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 …
Proximal alternating-direction-method-of-multipliers-incorporated nonnegative latent factor analysis
High-dimensional and incomplete (HDI) data subject to the nonnegativity constraints are
commonly encountered in a big data-related application concerning the interactions among …
commonly encountered in a big data-related application concerning the interactions among …
An inherently nonnegative latent factor model for high-dimensional and sparse matrices from industrial applications
High-dimensional and sparse (HiDS) matrices are commonly encountered in many big-data-
related and industrial applications like recommender systems. When acquiring useful …
related and industrial applications like recommender systems. When acquiring useful …
Large-scale and scalable latent factor analysis via distributed alternative stochastic gradient descent for recommender systems
Latent factor analysis (LFA) via stochastic gradient descent (SGD) is highly efficient in
discovering user and item patterns from high-dimensional and sparse (HiDS) matrices from …
discovering user and item patterns from high-dimensional and sparse (HiDS) matrices from …
Convergence analysis of single latent factor-dependent, nonnegative, and multiplicative update-based nonnegative latent factor models
A single latent factor (LF)-dependent, nonnegative, and multiplicative update (SLF-NMU)
learning algorithm is highly efficient in building a nonnegative LF (NLF) model defined on a …
learning algorithm is highly efficient in building a nonnegative LF (NLF) model defined on a …