
Quantification of Carbon Sequestration in Urban Forests
Vegetation, trees in particular, sequester carbon by absorbing carbon di...
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Central Limit Theory for Linear Spectral Statistics of Normalized Separable Sample Covariance Matrix
This paper focuses on the separable covariance matrix when the dimension...
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Factor Modelling for Clustering Highdimensional Time Series
We propose a new unsupervised learning method for clustering a large num...
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PAIRS AutoGeo: an Automated Machine Learning Framework for Massive Geospatial Data
An automated machine learning framework for geospatial data named PAIRS ...
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PhysicsInformed Neural Network Super Resolution for AdvectionDiffusion Models
Physicsinformed neural networks (NN) are an emerging technique to impro...
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Monitoring the Impact of Wildfires on Tree Species with Deep Learning
One of the impacts of climate change is the difficulty of tree regrowth ...
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Lifelong Object Detection
Recent advances in object detection have benefited significantly from ra...
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Robust Covariance Estimation for Highdimensional Compositional Data with Application to Microbial Communities Analysis
Microbial communities analysis is drawing growing attention due to the r...
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Statistical inference in massive datasets by empirical likelihood
In this paper, we propose a new statistical inference method for massive...
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Generalizable Resource Allocation in Stream Processing via Deep Reinforcement Learning
This paper considers the problem of resource allocation in stream proces...
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On eigenvalues of a highdimensional spatialsign covariance matrix
Sample spatialsign covariance matrix is a muchvalued alternative to sa...
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TracyWidom limit for the largest eigenvalue of highdimensional covariance matrices in elliptical distributions
Let X be an M× N random matrices consisting of independent Mvariate ell...
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Performance Estimation of Synthesis Flows cross Technologies using LSTMs and Transfer Learning
Due to the increasing complexity of Integrated Circuits (ICs) and System...
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Highdimensional covariance matrices in elliptical distributions with application to spherical test
This paper discusses fluctuations of linear spectral statistics of high...
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High Dimensional Elliptical Sliced Inverse Regression in nonGaussian Distributions
Sliced inverse regression (SIR) is the most widelyused sufficient dimen...
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Distribution Regression
Linear regression is a fundamental and popular statistical method. There...
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Wang Zhou
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