Sökning: "greedy"
Visar resultat 1 - 5 av 56 avhandlingar innehållade ordet greedy.
1. On Directed Random Graphs and Greedy Walks on Point Processes
Sammanfattning : This thesis consists of an introduction and five papers, of which two contribute to the theory of directed random graphs and three to the theory of greedy walks on point processes. We consider a directed random graph on a partially ordered vertex set, with an edge between any two comparable vertices present with probability p, independently of all other edges, and each edge is directed from the vertex with smaller label to the vertex with larger label. LÄS MER
2. Greedy Algorithms for Distributed Compressed Sensing
Sammanfattning : Compressed sensing (CS) is a recently invented sub-sampling technique that utilizes sparsity in full signals. Most natural signals possess this sparsity property. From a sub-sampled vector, some CS reconstruction algorithm is used to recover the full signal. LÄS MER
3. New results about the approximation behavior of the greedy triangulation
Sammanfattning : In this paper it is shown that there is some constant c, such that for any polygon, with or without holes, with w concave vertices, the length of any greedy triangulation of the polygon is not longer than c x (w + 1) times the length of a minimum weight triangulation of the polygon (under the assumption that no three vertices lie on the same line). A low approximation constant is proved for interesting classes of polygons. LÄS MER
4. Analysis of Algorithms for Combinatorial Auctions and Related Problems
Sammanfattning : The thesis consists of four papers on combinatorial auctions and a summary. The first part is more of a practical nature and contains two papers. In the first paper, we study the performance of a caching technique in an optimal algorithm for a multi-unit combinatorial auction. LÄS MER
5. Cooperative Compressive Sampling
Sammanfattning : Compressed Sampling (CS) is a promising technique capable of acquiring and processing data of large sizes efficiently. The CS technique exploits the inherent sparsity present in most real-world signals to achieve this feat. Most real-world signals, for example, sound, image, physical phenomenon etc., are compressible or sparse in nature. LÄS MER