Now showing items 101-110 of 311
Development of Tools for Analyzing and Sharing Proteomics Data
(The University of Bergen, 2010-03-22)
A matrix-free method for regularisation with unrestricted variables
(The University of Bergen, 2008)
In this thesis a method for the partially norm constrained least squares problem is presented. The method relies on a large-scale trust-region solver and has a low storage requirement. A combination of image misalignment ...
Improving Parallel Sparse Matrix-vector Multiplication
(The University of Bergen, 2013-12-19)
Sparse Matrix-vector Multiplication (SMvM) is a mathematical technique encountered in many programs and computations and is often heavily used. Solving SMvM in parallel allows for bigger instances to be solved, and problems ...
Exact algorithms for treewidth and minimum fill-in
(SIAM Journals, 2006)
Finding k Disjoint Triangles in an Arbitrary Graph
(Springer Verlag, 2004)
QALM - a tool for automating quantitative analysis of LC-MS-MS/MS data
(The University of Bergen, 2010-05-31)
The goal of bioinformatics is to support science and research in the field of biology through the application of information technology. Proteomics is a field within biology that deals with the study of proteins. This paper ...
Datainnsamling med XForms i Dynamic Presentation Generator
(The University of Bergen, 2011-06-01)
A Comparison of Vertex and Edge Partitioning Approaches for Parallel Maximal Matching
(The University of Bergen, 2013-12-09)
This thesis will compare two ways of distributing data for parallel graph algorithms: vertex and edge partitioning, using a distributed memory system. Previous studies on the parallelization of graphs has often been ...
A type system for counting instances of software components
We identify an abstract language for component software based on process algebra. Besides the usual operators for sequential, alternative and parallel composition, it has primitives for instantiating components and for ...
On a New Method for Derivative Free Optimization
A new derivative-free optimization method for unconstrained optimization of partially separable functions is presented. Using average curvature information computed from sampled function values the method generates an ...