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We discuss applications to class numbers and conjugacy class zeta functions of p-groups and unipotent group schemes, respectively.doi:10.1016/j.jpaa.2019.106203Tobias RossmannJournal of Pure and Applied AlgebraT. Rossmann. "The average size of the kernel of a matrix and or- bits of linear ...
Kernel densities provide a useful means of judging whether a set of results from a round of a proficiency test is unimodal or multimodal and, in either case, estimating the values of the identified mode, modes, or shoulders. The judgment of whether a data set is multimodal depends on having...
2024: "Android Binder Attack Matrix" by Utkarsh [article] [part 2] [part 3] [part 4] [part 5]2024: "Driving forward in Android drivers" by Seth Jenkins [article] [video] [CVE-2023-32837] [CVE-2023-32832]2024: "Attacking Android Binder: Analysis and Exploitation of CVE-2023-20938" ...
A hierarchical matrix is an efficient data-sparse representation of a matrix, especially useful for large dimensional problems. It consists of low-rank subblocks leading to low memory requirements as well as inexpensive computational costs. In this work, we discuss the use of the hierarchical matrix...
A theoretical understanding of generalization remains an open problem for many machine learning models, including deep networks where overparameterization leads to better performance, contradicting the conventional wisdom from classical statistics. Here,
Let A be a positive definite l×l matrix. Then κ(x,y)=xTAy is a kernel. • If κ1(x,y):X×X⟼R, then κ(x,y)=exp(κ1(x,y)) is also a kernel, and if p(⋅) is a polynomial with nonnegative coefficients, κ(x,y)=p(κ1(x,y)) is also a kernel. The in...
The above method is closely related to the power method used to compute the largest eigenvalue of a matrix [49]. Efficient pre-conditioners may also be used to speed up convergence as shown by [49]; since each iteration of (46) involves the calculation of the matrix–vector product W×xt...
Use this library of math routines for compute-intensive tasks: linear algebra, FFT, RNG. Optimized for high-performance computing and data science.
Calculate a kernel covariance matrix.params