We present an efficient implementation of the Modified SParse Approximate Inverse (MSPAI) preconditioner. MSPAI generalizes the class of preconditioners based on Frobenius norm mi...
Thomas Huckle, A. Kallischko, A. Roy, M. Sedlacek,...
The solution of large-scale, nonlinear PDE-based simulations typically depends on the performance of sparse linear solvers, which may be invoked at each nonlinear iteration. We pre...
Sanjukta Bhowmick, Lois C. McInnes, Boyana Norris,...
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...
It is well-known that two-level and multi-level preconditioned conjugate gradient (PCG) methods provide efficient techniques for solving large and sparse linear systems whose coeff...
J. M. Tang, S. P. MacLachlan, Reinhard Nabben, C. ...
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...