Results 61 to 70 of about 1,917,955 (191)
A projective approach to nonnegative matrix factorization
, 2021 In data science and machine learning, the method of nonnegative matrix factorization (NMF) is a powerful tool that enjoys great popularity. Depending on the concrete application, there exist several subclasses each of which performs a NMF under certain ...
Groetzner, Patrick
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The Distributional Effects of Economic Uncertainty*
International Economic Review, EarlyView.ABSTRACT We study the distributional implications of uncertainty shocks by developing a model that links macroeconomic aggregates to the US distribution of earnings and consumption. Our findings suggest that the fraction of low‐earning workers decreases initially, while the share of households reporting low consumption increases.
Florian Huber +2 more
wiley +1 more source
Using underapproximations for sparse nonnegative matrix factorization [PDF]
Nonnegative Matrix Factorization (NMF) has gathered a lot of attention in the last decade and has been successfully applied in numerous applications.
GILLIS, Nicolas, GLINEUR, François
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A Quantile Model of Firm Investment
International Economic Review, EarlyView.ABSTRACT Are firms risk averse? We propose a dynamic model of firm investment under uncertainty that captures firms' risk attitudes through quantile preferences. The firm maximizes its present value, defined as current profits and investment plus the discounted value of the τ$\tau$‐quantile of its value next period.
Heitor Almeida +3 more
wiley +1 more source
Journal of King Saud University: Computer and Information SciencesCommunity detection is a key task for revealing functional organization in complex networks. Graph neural networks (GNNs) capture non-linear relationships but often suffer from over-smoothing as layers increase.
Shunli Li, Ling Wang, Mingjun Bai
doaj +1 more source
Nonnegative factorization and the maximum edge biclique problem [PDF]
Nonnegative matrix factorization (NMF) is a data analysis technique based on the approximation of a nonnegative matrix with a product of two nonnegative factors, which allows compression and interpretation of nonnegative data. In this paper, we study the
GILLIS, Nicolas, GLINEUR, François
core
On the effect of the perturbation of a nonnegative matrix on its Perron eigenvector [PDF]
, 1982 Elsner L, Johnson CR, Neumann MM. On the effect of the perturbation of a nonnegative matrix on its Perron eigenvector. Czechoslovak Mathematical Journal.
Elsner, Ludwig F. +5 more
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A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces
International Statistical Review, EarlyView.Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri +3 more
wiley +1 more source
Measure‐valued processes for energy markets
Mathematical Finance, Volume 35, Issue 2, Page 520-566, April 2025.Abstract We introduce a framework that allows to employ (non‐negative) measure‐valued processes for energy market modeling, in particular for electricity and gas futures. Interpreting the process' spatial structure as time to maturity, we show how the Heath–Jarrow–Morton approach can be translated to this framework, thus guaranteeing arbitrage free ...
Christa Cuchiero +3 more
wiley +1 more source
On the geometric interpretation of the nonnegative rank [PDF]
The nonnegative rank of a nonnegative matrix is the minimum number of nonnegative rank-one factors needed to reconstruct it exactly. The problem of determining this rank and computing the corresponding nonnegative factors is difficult; however it has ...
GILLIS, Nicolas, GLINEUR, François
core