Results 11 to 20 of about 121 (92)
Clinical and Translational Discovery, Volume 6, Issue 4, August 2026.Multi‐endpoint clinical trials face long‐standing statistical challenges. Vector‐based comparison (VBC) decomposes endpoints into orthogonal components. Applied to five clinical trials, it reduced confidence‐interval widths by about 50%, indicating higher statistical power, without altering the clinical meaning of endpoints.
Maria Kokkali, Vangelis D. Karalis
wiley +1 more source
Efficient Tensor Completion Algorithms for Highly Oscillatory Operators
Numerical Linear Algebra with Applications, Volume 33, Issue 4, August 2026.ABSTRACT We address the problem of recovering highly oscillatory operators, represented as n×n$$ n\times n $$ matrices with a fixed set of observed entries. Given that these matrices can be well compressed by butterfly matrix decomposition of L=𝒪(logn) levels requiring only O(nlogn)$$ O\left(n\log n\right) $$ degrees of freedom, we propose a novel ...
Navjot Singh +3 more
wiley +1 more source
Randomized Algorithms for Streaming Low‐Rank Approximation in Tree Tensor Network Format
Numerical Linear Algebra with Applications, Volume 33, Issue 4, August 2026.ABSTRACT In this work, we present the tree tensor network Nyström (TTNN), an algorithm that extends recent research on streamable tensor approximation, such as for Tucker and tensor‐train formats, to the more general tree tensor network format, enabling a unified treatment of various existing methods.
Alberto Bucci, Gianfranco Verzella
wiley +1 more source
The Use of Restarted Krylov Methods for Large Sparse Least Squares Problems
Numerical Linear Algebra with Applications, Volume 33, Issue 4, August 2026.ABSTRACT The use of restarted Krylov methods for solving large sparse linear least squares problems suffers from certain inherited difficulties. One of them arises in ill‐conditioned problems, when part of the residual vector is spanned by singular vectors that correspond to small singular values.
Achiya Dax
wiley +1 more source
Mixed Precision Augmented GMRES
Numerical Linear Algebra with Applications, Volume 33, Issue 4, August 2026.ABSTRACT We aim to accelerate the restarted generalized minimal residual (GMRES) method for the solutions of linear systems by combining two types of techniques. On the one hand, mixed precision GMRES algorithms, which use lower precision in certain steps of the inner cycles, offer significant reductions in computational and memory costs.
Yongseok Jang +2 more
wiley +1 more source
Advanced Physics Research, Volume 5, Issue 7, July 2026.ABSTRACT We introduce a family of bosonic quantum error‐correcting codes built as a rotation‐symmetric superposition of squeezed vacuum states, which promise protection against both loss and dephasing noise channels. The robustness of these “squeezed‐vacuum codes” arises from being arranged at evenly spaced angles in phase‐space, and simultaneously in ...
Nir Gutman +4 more
wiley +1 more source
Solid Mechanics Segregated Solver Acceleration With Jacobian‐Free Newton‐Krylov
International Journal for Numerical Methods in Engineering, Volume 127, Issue 11, 15 June 2026.ABSTRACT The segregated algorithm is a common approach for finite volumes solvers in solid mechanics, providing a memory‐efficient and straightforward implementation. Due to the inter‐coupling of the components through the source terms, it suffers from a slow convergence behavior in specific scenarios, such as geometries with significantly uneven ...
Andry Monlon +5 more
wiley +1 more source
Journal of Chemometrics, Volume 40, Issue 6, June 2026.ABSTRACT Partial least squares (PLS) regression is widely used for multivariate calibration in high‐dimensional and collinear settings. However, classical PLS relies on least squares optimization and is therefore sensitive to anomalous observations, leverage points, and structured spectral interferences.
Puneet Mishra
wiley +1 more source
Row‐Aware Randomized SVD With Applications
Numerical Linear Algebra with Applications, Volume 33, Issue 3, June 2026.ABSTRACT The randomized singular value decomposition proposed in [28] has certainly become one of the most well‐established randomization‐based algorithms in numerical linear algebra. The key ingredient of the entire procedure is the computation of a subspace which is close to the column space of the target matrix A∈ℝm×n$$ \mathbf{A}\in {\mathbb{R}}^{m\
Davide Palitta, Sascha Portaro
wiley +1 more source
Gram Decay and Intrinsic Dimensions of Krylov Subspaces
Numerical Linear Algebra with Applications, Volume 33, Issue 3, June 2026.ABSTRACT Krylov subspace methods solve large sparse linear systems Ax=b$$ Ax=b $$ by building a sequence of polynomial approximations to A−1b$$ {A}^{-1}b $$ from successive matrix‐vector products. In finite precision, the number of numerically independent directions that can be extracted from this sequence is bounded by the intrinsic information ...
Stephen J. Thomas
wiley +1 more source