Results 31 to 40 of about 150,538 (265)

The Eigenspace Spectral Regularization Method for Solving Discrete Ill-Posed Systems

Journal of Applied Mathematics, 2021
This paper shows that discrete linear equations with Hilbert matrix operator, circulant matrix operator, conference matrix operator, banded matrix operator, TST matrix operator, and sparse matrix operator are ill-posed in the sense of Hadamard.
Fredrick Asenso Wireko, Benedict Barnes, Charles Sebil, Joseph Ackora-Prah   +3 more
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

Spatial and single‐nuclei transcriptomics reveals idiosyncratic and generic patterns in papillary and anaplastic thyroid cancers

Molecular Oncology, EarlyView.
Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur, Joel Rodrigues Vitória, Manuel Saiselet, Ligia Craciun, Denis Larsimont, Anne Lefort, Frédérick Libert, Carine Maenhaut, Sabine Costagliola, Maxime Tarabichi, Mirian Romitti, Vincent Detours   +11 more
wiley   +1 more source

Probability Matrix Decomposition Models [PDF]

Psychometrika, 1996
In this paper, we consider a class of models for two-way matrices with binary entries of 0 and 1. First, we consider Boolean matrix decomposition , conceptualize it as a latent response model (LRM) and, by making use of this conceptualization ...
Maris, E., DeBoeck, P., Mechelen, I. van
openaire   +2 more sources

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

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

Arbitrary decomposition of a Mueller matrix [PDF]

Optics Letters, 2019
Mueller polarimetry involves a variety of instruments and technologies whose importance and scope of applications are rapidly increasing. The exploitation of these powerful resources depends strongly on the mathematical models that underlie the analysis and interpretation of the measured Mueller matrices and, very particularly, on the theorems for ...
José J. Gil, Ignacio San José
openaire   +5 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

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

Single‐cell DNA methylation profiling: Technologies, computation, and applications in precision oncology

Molecular Oncology, EarlyView.
Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley   +1 more source