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Related Articles from SNS
Directional bone matrix mineralization in the CAM assay is governed by vascular integration and matrix remodeling
Bone matrix mineralization plays an important role in maintaining bone health but is a highly dynamic process for which few physiologically relevant model systems exist. The chorioallantoic membrane (CAM) assay is one such assay and has been used to study biomineralization; however, the mechanisms controlling mineral deposition in the CAM assay remain poorly understood. Here, we implanted decellularized, organic bone matrices onto the CAM and investigated their mineralization using a...
An indefinite LOBPCG type of algorithm for detecting a definite Hermitian matrix pair
Announce Type: new Abstract: A Hermitian matrix pair $(A,B)$ is called definite if some real linear combination of the matrices $A$ and $B$ is a positive definite matrix. Detection of the definiteness is not straightforward. We propose a basic subspace algorithm for detecting a large definite matrix pair $(A,B)$ with indefinite $B$. The proposed subspace algorithm is based on iterative testing of small projected Hermitian matrix pairs formed by using subspaces of small dimensions.
Low-rank Distributional Matrix Completion
arXiv:2606.04176v1 Announce Type: new Abstract: We study a distributional generalization of the matrix completion problem in which each entry of the target matrix is a probability distribution rather than a scalar. In this setting, only a subset of matrix entries is observed, and even for observed entries, the underlying distributions are not directly accessible; instead, we observe finitely many samples drawn from them. To represent distributional entries, we employ kernel mean embeddings...
Nuclear confinement from matrix stiffness drives epigenomic reprogramming of gingival fibroblasts
Periodontal disease is characterized by progressive degradation of the gingival extracellular matrix and loss of the physical confinement it imposes on resident stromal cells. In human periodontal tissue, ECM collagen integrity is inversely correlated with facultative nuclear histone acetylation in stromal cells. We hypothesized that matrix stiffness directly coordinates an epigenomic shift in stromal cells.
When Good Enough Is Optimal: Multiplication-Only Matrix Inversion Approximation for Quantized Gated DeltaNet
Announce Type: new Abstract: Matrix inversion in chunk-wise parallel linear attention is a major bottleneck for long-context modeling, particularly on NPUs, where forward-substitution-based methods exhibit limited parallelism and poor hardware utilization. We propose a fast, Matrix Multiplication (MatMul)-based algorithm tailored for strictly lower-triangular matrices arising in chunk-wise linear attention. Motivated by the rapid growth of Neumann-series terms and the diagonal concentration...
Rectangular Matrix Multiplication in the Low-Bandwidth Model
arXiv:2606.04652v1 Announce Type: new Abstract: We study rectangular matrix multiplication in the low-bandwidth model of distributed computing. There are $n$ computers; initially the input matrices are distributed evenly between computers, and in each communication round every computer can send and receive an $O(\log n)$-bit message. Eventually each computer must output its designated part of the product matrix.
FalconGEMM: Surpassing Hardware Peaks with Lower-Complexity Matrix Multiplication
arXiv:2605.06057v3 Announce Type: replace Abstract: Peak breaking Matrix Multiplication is a promising technique to improve the performance of DL, especially in LLM training and inference. We present FalconGEMM, a cross-platform framework that automates the deployment, optimization, and selection of Lower-Complexity Matrix Multiplication Algorithms (LCMAs) across diverse hardware. There are three key innovations: (1) a Deployment Module that enables portable execution across various hardware...
Latent Structural Categorical Matrix Completion with Application to Quasispecies Analysis
Announce Type: cross Abstract: Matrix completion has been extensively studied for real-valued data, but existing methods are often limited in handling categorical variables. We propose LCMC, a double-loop optimization framework for categorical matrix completion via latent factorization based on a binary tensor representation. In this setting, each categorical entry is encoded as a one-hot vector along a third tensor mode, thereby preserving its discrete, non-ordinal nature.
A Nonmonotone Gradient-Based Algorithm for Symmetric Nonnegative Matrix Factorization and Graph Clustering
arXiv:2606.02887v1 Announce Type: new Abstract: Symmetric nonnegative matrix factorization (Symmetric NMF) approximates a matrix as $WW^T$ with nonnegative rectangular factor $W$. It has broad applications in graph clustering and machine learning. In contrast to the NMF, projected gradient methods for the symmetric problem had been associated with slow convergence.
Algebraic and FFT-Based Methods for Discrete-Time Matrix Convolutions with Applications to Semi-Markov Models
arXiv:2605.30379v1 Announce Type: new Abstract: We study the convolution product of matrix-valued sequences and its role in the computation of Markov renewal equations. Explicit representations and recursive formulae for the convolutional inverse are derived and used to construct FFT-accelerated convolution and Newton-type inversion schemes, together with a Gauss--Jordan alternative in truncated power-series rings. The proposed framework is also applied to discrete approximations of matrix...