We are interested in a general alpha matting approach for the simultaneous extraction of multiple image layers; each layer may have disjoint segments for material matting not limi...
We present a generalized subgraph preconditioning (GSP) technique to solve large-scale bundle adjustment problems efficiently. In contrast with previous work which uses either di...
We will present a matrix framework for the conjugate gradient methods, which is expressed in terms of whole vector sequences instead of single vectors or initial parts of sequence...
Eduardo F. D'Azevedo, Victor Eijkhout, Charles H. ...
We introduce a new preconditioner for solving a symmetric Toeplitz system of equations by the conjugate gradient method. This choice leads to an algorithm which is particularly sui...
The finite difference discretization of the Poisson equation in three dimensions results in a large, sparse, and highly structured system of linear equations. This prototype prob...
It was recently shown that block-circulant preconditioners applied to a conjugate gradient method used to solve structured sparse linear systems arising from 2D or 3D elliptic prob...
Adding on-chip decoupling capacitors (decaps) is an effective way to reduce voltage noise in power/ground networks and ensure robust power delivery. In this paper, we present a fa...
Zhenyu Qi, Hang Li, Sheldon X.-D. Tan, Lifeng Wu, ...
We consider the problem of solving a symmetric, positive definite system of linear equations. The most well-known and widely-used method for solving such systems is the preconditi...
The advances in kernel-based learning necessitate the study on solving a large-scale non-sparse positive definite linear system. To provide a deterministic approach, recent resear...
Compressed sensing or compressive sampling (CS) has been receiving a lot of interest as a promising method for signal recovery and sampling. CS problems can be cast as convex prob...
Seung-Jean Kim, Kwangmoo Koh, Michael Lustig, Step...