Results 91 to 100 of about 7,174 (250)
Parallel Nonnegative Matrix Factorization with Manifold Regularization
Journal of Electrical and Computer Engineering, 2018 Nonnegative matrix factorization (NMF) decomposes a high-dimensional nonnegative matrix into the product of two reduced dimensional nonnegative matrices.
Fudong Liu, Zheng Shan, Yihang Chen
doaj +1 more source
A Quantised Push‐Sum Distributed Adaptive Momentum Algorithm for Optimisation Over Directed Networks
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT In this paper, we investigate a distributed constrained optimisation problem over directed networks. The agents in the networks conduct local computations and communications, endeavouring to collaboratively minimise the aggregation of all locally known convex cost functions subject to a global constraint set.
Qingguo Lü +6 more
wiley +1 more source
IEEE AccessNonnegative matrix factorization (NMF) is an effective dimensionality reduction and representation learning technique that captures the intrinsic structure of nonnegative data by learning low-dimensional, parts-based representations.
Xuzhu Shen, Jie Li
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A Label-Embedding Online Nonnegative Matrix Factorization Algorithm
IEEE Access, 2019 Nonnegative matrix factorization is a widely used data processing method, which has been applied in many fields, such as data dimension reduction and feature extraction.
Zhibo Guo, Ying Zhang
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The British Journal of Sociology, EarlyView.ABSTRACT The 2000s have witnessed a significant, worldwide boom in new art museums founded by private, wealthy collectors. While the arts have long been a key arena for the remaking of elite distinction and the reproduction of inequalities, this surge in private museums has sparked much controversy.
Sara de Andrade Silva +2 more
wiley +1 more source
, 2010 This is the author's accepted pre-print of the article, first published as M. D. Plumbley, A. Cichocki and R. Bro. Non-negative mixtures. In P. Comon and C. Jutten (Ed), Handbook of Blind Source Separation: Independent Component Analysis and Applications.
M. D. Plumbley +9 more
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Graph‐Laplacian modeling of spatiotemporal effects for house price estimation
Real Estate Economics, EarlyView.Abstract Many variables involve the modeling of spatial effects, and their dynamics over time. This article presents a linear model in which spatiotemporal random effects are modeled by graph‐Laplacians. A graph‐Laplacian flexibly encodes adjacency in both space and time, in our case not depending on unknown parameters. The graph‐Laplacian can be input
Willem P Sijp, Marc K. Francke
wiley +1 more source
When in Doubt, Tax More Progressively? Uncertainty and Progressive Income Taxation
International Economic Review, EarlyView.ABSTRACT We study the optimal income tax problem under parameter uncertainty about household preferences and wage dynamics. We derive conditions characterizing how such uncertainty affects optimal tax policy. To quantify the effect, we estimate a life‐cycle model using US data and a Bayesian approach.
Minsu Chang, Chunzan Wu
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Sequentially-fit alternating least squares algorithms in nonnegative matrix factorization
, 2010 Nonnegative matrix factorization (NMF) and nonnegative least squares regression (NNLS regression) are widely used in the physical sciences; this thesis explores the often-overlooked origins of NMF in the psychometrics literature.
Lorenz, Florian M.
core
The Legacy of Policy Inaction in Climate‐Growth Models
International Economic Review, EarlyView.ABSTRACT To better understand the structure and core mechanisms of a broad class of climate‐growth models, we study a simplified version of the dynamic integrated model of climate and the economy (DICE) through the lens of growth theory. We analytically show that this model features a continuum of saddle‐point stable steady states.
Thomas Steger, Timo Trimborn
wiley +1 more source