Fast approximate truncated SVD
نویسندگان
چکیده
منابع مشابه
Comparison of Truncated SVD and Jacobi-Davidson SVD within ESVDMOR
The reduction of parasitic linear subcircuits is one of many issues in model order reduction (MOR) for VLSI design. This issue is well explored, but the structure of these subcircuits has been changing recently. So far, the number of elements in these subcircuits was significantly larger than the number of connections to the whole circuit, the so called pins or terminals. This assumption is no ...
متن کاملQUIC-SVD: Fast SVD Using Cosine Trees
The Singular Value Decomposition is a key operation in many machine learning methods. Its computational cost, however, makes it unscalable and impractical for applications involving large datasets or real-time responsiveness, which are becoming increasingly common. We present a new method, QUIC-SVD, for fast approximation of the whole-matrix SVD based on a new sampling mechanism called the cosi...
متن کاملFaster SVD-Truncated Least-Squares Regression
We develop a fast algorithm for computing the “SVD-truncated” regularized solution to the leastsquares problem: minx ‖Ax − b‖2. Let Ak of rank k be the best rank k matrix computed via the SVD of A. Then, the SVD-truncated regularized solution is: xk = A † k b. If A is m × n, then, it takes O(mnmin{m,n}) time to compute xk using the SVD of A. We give an approximation algorithm for xk which const...
متن کاملParallel Svd{updating Using Approximate Rotations
In this paper a parallel implementation of the SVD{updating algorithm using approximate rotations is presented. In its original form the SVD{updating algorithm had numerical problems if no reorthogonalization steps were applied. Representing the orthogonal matrix V (right singular vectors) using its parameterization in terms of the rotation angles of n(n?1)=2 plane rotations these reorthogonali...
متن کاملA GPU-Based Approximate SVD Algorithm
Approximation of matrices using the Singular Value Decomposition (SVD) plays a central role in many science and engineering applications. However, the computation cost of an exact SVD is prohibitively high for very large matrices. In this paper, we describe a GPU-based approximate SVD algorithm for large matrices. Our method is based on the QUIC-SVD introduced by [6], which exploits a tree-base...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Numerical Linear Algebra with Applications
سال: 2019
ISSN: 1070-5325,1099-1506
DOI: 10.1002/nla.2246