Results 61 to 70 of about 4,500,411 (350)

Asset Allocation Strategies Using Covariance Matrix Estimators

Acta Universitatis Sapientiae: Economics and Business, 2022
The covariance matrix is an important element of many asset allocation strategies. The widely used sample covariance matrix estimator is unstable especially when the number of time observations is small and the number of assets is large or when high ...
László PáL
doaj   +1 more source

High-Dimensional Covariance Estimation via Constrained L_q-Type Regularization

Mathematics, 2023
High-dimensional covariance matrix estimation is one of the fundamental and important problems in multivariate analysis and has a wide range of applications in many fields.
Xin Wang, Lingchen Kong, Liqun Wang, Zhaoqilin Yang   +3 more
doaj   +1 more source

Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization [PDF]

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2017
Global covariance pooling in convolutional neural networks has achieved impressive improvement over the classical first-order pooling. Recent works have shown matrix square root normalization plays a central role in achieving state-of-the-art performance.
P. Li, Jiangtao Xie, Qilong Wang, Zilin Gao   +3 more
semanticscholar   +1 more source

Covariance matrix estimation methods for constrained portfolio optimization in a South African setting [PDF]

, 2010
One of the major topics of concern in Modern Portfolio Theory is portfolio optimization which is centred on the mean-variance framework. In order for this framework to be implemented, esti- mated parameters (covariance matrix for the constrained portfo ...
Madume, Jaison Pezisai
core   +1 more source

Missing Covariance Matrix Recovery with the FDA-MIMO Radar Using Deep Learning Method

Leida xuebao, 2023
The realization of anti-jamming technologies via beamforming for applications in Frequency-Diverse Arrays and Multiple-Input and Multiple-Output (FDA-MIMO) radar is a field that is undergoing intensive research.
Zihang DING, Junwei XIE, Bo WANG
doaj   +1 more source

Automatic positive semidefinate HAC covariance matrix and GMM estimation [PDF]

, 2005
This paper proposes a new class of heteroskedastic and autocorrelation consistent (HAC) covariance matrix estimators. The standard HAC estimation method reweights estimators of the autocovariances.
Smith, Richard J.
core   +1 more source

A covariance matrix test for high-dimensional data [PDF]

Songklanakarin Journal of Science and Technology (SJST), 2016
For the multivariate normally distributed data with the dimension larger than or equal to the number of observations, or the sample size, called high-dimensional normal data, we proposed a test for testing the null hypothesis that the covariance matrix
Saowapha Chaipitak, Samruam Chongcharoen
doaj   +1 more source

Over-sampling imbalanced datasets using the Covariance Matrix [PDF]

EAI Endorsed Transactions on Energy Web, 2020
INTRODUCTION: Nowadays, many machine learning tasks involve learning from imbalanced datasets,leading to the miss-classification of the minority class. One of the state-of-the-art approaches to ”solve” thisproblem at the data level is Synthetic Minority ...
Ireimis Leguen-deVarona, Julio Madera, Yoan Martínez-López, José Hernández-Nieto   +3 more
doaj   +1 more source

Profiling neoadjuvant therapy response in rectal cancer using meta‐analysis of publicly available transcriptomic RNA‐seq datasets

Molecular Oncology, EarlyView.
This study integrates publicly available transcriptomic datasets to identify molecular signatures associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. By analyzing a combination of multiple cohorts with bioinformatics approaches, we reveal biological pathways and immune‐related features that may improve ...
Aleksandra Stanojevic, Rafael Stroggilos, Mladen Marinkovic, Ana Djuric, Suzana Stojanovic‐Rundic, Radmila Jankovic, Sergi Castellvi‐Bel, Remond J.A. Fijneman, Antonia Vlahou, Jerome Zoidakis, Milena Cavic   +10 more
wiley   +1 more source

Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani, Emmanuel Barbeau, Béatrice Lemesle, Emilie Milongo‐Rigal, Sophie Fernandez, Sandrine Charpentier, Jean‐François Albucher, Nicolas Raposo, Fabrice Bonneville, Patrice Péran, Jérémie Pariente   +10 more
wiley   +1 more source