Results 81 to 90 of about 26,367 (267)
Coordinate transformation parameters in Nepal by using neural network and SVD methods
Journal of Geodetic Science, 2019 The present study computes B-W extension model (extended Bursa-Wolf model) coordinate transformation parameters from World Geodetic System 1984 (WGS-84) to the Everest datum namely Everest (1830) and Everest (1956) using records of coordinate ...
Ansari Kutubuddin +3 more
doaj +1 more source
SVD-matching using SIFT features
Graphical Models, 2006 The paper tackles the problem of feature points matching between pair of images of the same scene. This is a key problem in computer vision. The method we discuss here is a version of the SVD-matching proposed by Scott and Longuet-Higgins and later modified by Pilu, that we elaborate in order to cope with large scale variations.
DELPONTE E +3 more
openaire +5 more sources
Dynamic survival risk prediction with time‐varying high‐dimensional images
Canadian Journal of Statistics, EarlyView.Abstract Integrating longitudinal data with survival models is a prevalent strategy for dynamic survival risk prediction while accounting for subjects' longitudinally observed variables. However, existing methods primarily focus on scalar longitudinal data and seldom tackle the complexities associated with high‐dimensional longitudinal imaging data ...
Bingfan Liu +7 more
wiley +1 more source
The Relation Between the EVD or SVD of Summands and the EVD or SVD of the Sum
CoRRIn this work, we show how the eigenstructures of summands are related to that of the sum. In particular, we show that the sum of two positive semidefinite matrices can be written as the inner product of two block matrices $\mathbf{C} = \mathbf{A} + \mathbf{B} = \mathbf{PD}^2\mathbf{P}^T + \mathbf{QE}^2\mathbf{Q}^T = \begin{pmatrix} \mathbf{PD} & ...
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Optimal subsampling for regression with mixed‐type predictors
Canadian Journal of Statistics, EarlyView.Abstract Subsampling has emerged as an appealing strategy to mitigate the computational and storage challenges imposed by large datasets. Recent subsampling techniques have shown notable computational gains for data dominated by numerical predictors. However, real‐world datasets frequently contain both numerical and categorical predictors.
Jiaqing Zhu, Lin Wang, Fasheng Sun
wiley +1 more source
Quenching the Hubbard Model: Comparison of Nonequilibrium Green's Function Methods
Contributions to Plasma Physics, EarlyView.ABSTRACT We benchmark nonequilibrium Green's function (NEGF) approaches for interaction quenches in the half‐filled Fermi–Hubbard model in one and two dimensions. We compare fully self‐consistent two‐time Kadanoff–Baym equations (KBE), the generalized Kadanoff–Baym ansatz (GKBA), and the recently developed NEGF‐based quantum fluctuations approach (NEGF‐
Jan‐Philip Joost +3 more
wiley +1 more source
Deep Underground Science and Engineering, EarlyView.The flowchart illustrates rock specimen testing, vibration signal acquisition, and feature extraction with Gaborlet and sparse filtering for classification. Abstract Traditional lithology identification methods mainly rely on core sampling and well‐logging data.
Jian Hao +5 more
wiley +1 more source
Вестник Дагестанского государственного технического университета: Технические наукиObjective. The paper defines the relevance of the task of increasing the efficiency of software, which in this case is understood as reducing the operating time of the designed software in the process of solving computationally complex problems.
A. Yu. Bezruchenko, V. A. Egunov
doaj +1 more source
Human action recognition based on back propagation neural network
网络与信息安全学报, 2017 For human action recognition,an algorithm for classifying human action based on back propagation (BP) neural network was proposed.Firstly,singular value decomposition (SVD) was used to extract the singular value of each frame of the video.Then each row ...
Jian ZOU
doaj +1 more source
Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives
CoRRWe provide a new LLM-compression solution via SVD, unlocking new possibilities for LLM compression beyond quantization and pruning. We point out that the optimal use of SVD lies in truncating activations, rather than merely using activations as an optimization distance.
Qinsi Wang +5 more
openaire +2 more sources