Campuses:

Algorithm

Tuesday, September 22, 2015 - 1:25pm - 2:25pm
Hui Zou (University of Minnesota, Twin Cities)
Distance weighted discrimination (DWD) is a margin-­based classifier with an interesting geometric motivation. DWD was originally proposed as a superior alternative to the support vector machine (SVM), however DWD is yet to be popular compared with the SVM. The main reasons are twofold. First, the state­-of­-the-­art algorithm for solving DWD is based on the second-­order-cone programming (SOCP), while the SVM is a quadratic programming problem which is much more efficient to solve.
Tuesday, June 2, 2015 - 2:30pm - 3:30pm
Simon King (Friedrich-Schiller-Universität)
The F5 algorithm is a signature based algorithm to compute Gröbner bases for modules over polynomial rings. The F5 signature allows to exploit commutativity relations in order to avoid redundant computations. When considering modules over path algebra quotients, one can instead exploit the quotient relations to avoid redundancies.
Wednesday, December 10, 2008 - 3:00pm - 3:40pm
Carl Kelley (North Carolina State University)
We will discuss a class of fast algorithms for linear and
nonlinear integral equations. These are two-level algorithms
based on the classic Atkinson-Brakhage method from the 1970s.
We will present more efficient approach which uses a matrix-free
Newton-Krylov iteration on the coarse mesh and does the
fine-to-coarse intergrid transfer with an average. We will then
apply the approach to the Ornstein-Zernike (OZ) equations for atomic
fluids and some extensions of the OZ equations for molecular fluids.
Thursday, October 2, 2008 - 2:00pm - 2:50pm
Chao Yang (Lawrence Berkeley Laboratory)
I will present a direct constrained minimization (DCM) algorithm
for solving the Kohn-Sham equations. The key ingredients of this
algorithm involve projecting the Kohn-Sham total energy functional
into a sequences of subspaces of small dimensions and seeking the
minimizer of total energy functional within each subspace. The
minimizer of a subspace energy functional not only provides a
search direction along which the KS total energy functional decreases
but also gives an optimal step-length to move along this search
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