Results 31 to 40 of about 150,142 (264)

Sparse Matrix Decompositions For Clustering [PDF]

, 2014
Publication in the conference proceedings of EUSIPCO, Lisbon, Portugal ...
openaire   +3 more sources

Singular-Value-Decomposition-Based Matrix Surgery

Entropy
This paper is motivated by the need to stabilise the impact of deep learning (DL) training for medical image analysis on the conditioning of convolution filters in relation to model overfitting and robustness.
Jehan Ghafuri, Sabah Jassim
doaj   +1 more source

Experimental validation of the reverse polar decomposition of depolarizing Mueller matrices [PDF]

Journal of the European Optical Society-Rapid Publications, 2007
We experimentally assess the validity of the reverse polar decomposition (R. Ossikovski et al., Opt. Lett. 32, 689 (2007)), which describes any Mueller matrix as a product of a depolarizer, a diattenuator and a retarder with the diattenuator placed after
Anastasiadou Makrina, Ben Hatit Sami, Ossikovski Razvigor, Guyot Steve, De Martino Antonello   +4 more
doaj   +1 more source

A Generalized CUR Decomposition for Matrix Pairs

SIAM Journal on Mathematics of Data Science, 2022
We propose a generalized CUR (GCUR) decomposition for matrix pairs $(A, B)$. Given matrices $A$ and $B$ with the same number of columns, such a decomposition provides low-rank approximations of both matrices simultaneously, in terms of some of their rows and columns.
Perfect Y. Gidisu, Michiel E. Hochstenbach   +1 more
openaire   +4 more sources

Interpreting the effects of DNA polymerase variants at the structural level

Molecular Oncology, EarlyView.
Using MAVISp and molecular dynamics simulations, we analyzed over 60 000 missense variants in POLE and POLD1 from ClinVar, COSMIC, cBioPortal, and saturation mutagenesis. Identified mechanistic indicators, including stability, binding, and long‐range, enable structural interpretation, providing ACMG‐like evidence for possible reclassification of VUS ...
Matteo Arnaudi, Karolina Krzesińska, Ludovica Beltrame, Pablo Sánchez‐Izquierdo Besora, Matteo Tiberti, Mef Nilbert, Anna Rohlin, Elena Papaleo   +7 more
wiley   +1 more source

Mueller matrix differential decomposition [PDF]

Optics Letters, 2011
We present a Mueller matrix decomposition based on the differential formulation of the Mueller calculus. The differential Mueller matrix is obtained from the macroscopic matrix through an eigenanalysis. It is subsequently resolved into the complete set of 16 differential matrices that correspond to the basic types of optical behavior for depolarizing ...
Ortega-Quijano, Noé, Arce-Diego, José Luis   +1 more
openaire   +3 more sources

Learnable Graph-Regularization for Matrix Decomposition

ACM Transactions on Knowledge Discovery from Data, 2023
Low-rank approximation models of data matrices have become important machine learning and data mining tools in many fields, including computer vision, text mining, bioinformatics, and many others. They allow for embedding high-dimensional data into low-dimensional spaces, which mitigates the effects of noise and uncovers latent relations.
Penglong Zhai, Shihua Zhang
openaire   +2 more sources

Mueller Matrix Decomposition and Image for Non-Destructive Testing of UAVs Skin

Applied Sciences, 2023
Recently, Mueller matrix polarimetry (MMP) has been widely applied in many aspects, such as radar target decomposition, monitoring the glucose level, tissue diagnostics, biological samples, etc., but it is still challenging for the complex light–matter ...
Hongzhe Li, Lin Li, Xiaolei Yu, Delong Meng, Ciyong Gu, Zhenlu Liu, Zhimin Zhao   +6 more
doaj   +1 more source

ZW4864‐mediated inhibition of the β‐catenin/BCL9/BCL9L complex reveals therapeutic potential in bladder cancer

Molecular Oncology, EarlyView.
BCL9 and BCL9L drive bladder cancer progression by enhancing β‐catenin signaling, promoting proliferation, migration, invasion, and organoid growth. Genetic depletion of BCL9(L) suppresses malignant phenotypes, while pharmacological disruption of the β‐catenin/BCL9(L) complex with ZW4864 inhibits canonical Wnt signaling and tumor‐associated cellular ...
Roland Kotolloshi, Mandy Berndt‐Paetz, Eileen Lerner, Gregoire Najjar, Anca Azoitei, Krishna Pal Singh, Shailendra Kumar Gupta, Olaf Wolkenhauer, Cagatay Günes, Otmar Huber, Marc‐Oliver Grimm, Daniel Steinbach   +11 more
wiley   +1 more source

Fast Circulant Tensor Power Method for High-Order Principal Component Analysis

IEEE Access, 2021
To understand high-order intrinsic key patterns in high-dimensional data, tensor decomposition is a more versatile tool for data analysis than standard flat-view matrix models. Several existing tensor models aim to achieve rapid computation of high-order
Taehyeon Kim, Yoonsik Choe
doaj   +1 more source