Latent Factor Modeling of scRNA-Seq Data Uncovers Dysregulated Pathways in Autoimmune Disease Patients
Sign Up to like & getrecommendations! Published in 2020 at "iScience"
DOI: 10.1016/j.isci.2020.101451
Abstract: Summary Latent factor modeling applied to single-cell RNA sequencing (scRNA-seq) data is a useful approach to discover gene signatures. However, it is often unclear what methods are best suited for specific tasks and how latent… read more here.
Keywords: scrna seq; factor modeling; latent factor; seq data ... See more keywords
Elastic-net regularized latent factor analysis-based models for recommender systems
Sign Up to like & getrecommendations! Published in 2019 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.10.046
Abstract: Abstract Latent factor analysis (LFA)-based models are highly efficient in recommender systems. The problem of LFA is defined on high-dimensional and sparse (HiDS) matrices corresponding to relationships among numerous entities in industrial applications. It is… read more here.
Keywords: latent factor; factor analysis; based models; factor ... See more keywords
Examining the latent factor structure of a hypothetical cigarette purchase task among pregnant women.
Sign Up to like & getrecommendations! Published in 2022 at "Experimental and clinical psychopharmacology"
DOI: 10.1037/pha0000571
Abstract: The cigarette purchase task (CPT) is a valid behavioral-economic measure of demand that has smokers estimate hypothetical cigarette consumption under a range of escalating prices. The task involves no experimenter exposure of participants to smoking.… read more here.
Keywords: task; cigarette; factor; pregnant women ... See more keywords
Fast and Accurate Non-Negative Latent Factor Analysis of High-Dimensional and Sparse Matrices in Recommender Systems
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2021.3125252
Abstract: 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 Momentum-incorporated Update (SLF-NM2U) algorithm, which enables its fast convergence. It is crucial to… read more here.
Keywords: non negative; analysis; high dimensional; latent factor ... See more keywords
A Second-Order Symmetric Non-Negative Latent Factor Model for Undirected Weighted Network Representation
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Network Science and Engineering"
DOI: 10.1109/tnse.2022.3206802
Abstract: Precise representation to undirected weighted network (UWN) is the foundation of understanding connection patterns inside a massive node set. It can be addressed via a Symmetric Non-negative Latent Factor (SNLF) model with a non-convex learning… read more here.
Keywords: order; model; second order; latent factor ... See more keywords
Generalized Nesterov's Acceleration-Incorporated, Non-Negative and Adaptive Latent Factor Analysis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Services Computing"
DOI: 10.1109/tsc.2021.3069108
Abstract: 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 knowledge from non-negative data represented by high-dimensional and sparse (HiDS) matrices arising… read more here.
Keywords: underline underline; non negative; nesterov acceleration; latent factor ... See more keywords
A Momentum-Accelerated Hessian-Vector-Based Latent Factor Analysis Model
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Services Computing"
DOI: 10.1109/tsc.2022.3177316
Abstract: Service-oriented applications commonly involve high-dimensional and sparse (HiDS) interactions among users and service-related entities, e.g., user-item interactions from a personalized recommendation services system. How to perform precise and efficient representation learning on such HiDS interactions… read more here.
Keywords: hessian vector; lfa; model; latent factor ... See more keywords
Assimilating Second-Order Information for Building Non-Negative Latent Factor Analysis-Based Recommenders
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2020.3002762
Abstract: A non-negative latent factor analysis (NLFA)-based recommender can make precise recommendations by correctly representing the non-negative characteristic of industrial data. It commonly relies on a nonconvex and bilinear optimization process, where the effects of first-order… read more here.
Keywords: factor analysis; negative latent; non negative; second order ... See more keywords
Inference on latent factor models for informative censoring
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DOI: 10.1177/09622802211057290
Abstract: This work discusses the problem of informative censoring in survival studies. A joint model for the time to event and the time to censoring is presented. Their hazard functions include a latent factor in order… read more here.
Keywords: factor models; inference latent; models informative; informative censoring ... See more keywords
Explore potential disease related metabolites based on latent factor model
Sign Up to like & getrecommendations! Published in 2022 at "BMC Genomics"
DOI: 10.1186/s12864-022-08504-w
Abstract: Background In biological systems, metabolomics can not only contribute to the discovery of metabolic signatures for disease diagnosis, but is very helpful to illustrate the underlying molecular disease-causing mechanism. Therefore, identification of disease-related metabolites is… read more here.
Keywords: latent factor; disease related; model; based latent ... See more keywords