Sökning: "Probability Distribution Modeling"
Visar resultat 16 - 20 av 70 avhandlingar innehållade orden Probability Distribution Modeling.
16. Spatial Spread of Organisms : Modeling ecological and epidemiological processes
Sammanfattning : This thesis focuses on the spread of organisms in both ecological and epidemiological contexts. In most of the studies presented, displacement is modeled with a spatial kernel function, which is characterized by scale and shape. These are measured by the net squared displacement (or kernel variance) and kurtosis, respectively. LÄS MER
17. Offline and Online Models for Learning Pairwise Relations in Data
Sammanfattning : Pairwise relations between data points are essential for numerous machine learning algorithms. Many representation learning methods consider pairwise relations to identify the latent features and patterns in the data. This thesis, investigates learning of pairwise relations from two different perspectives: offline learning and online learning. LÄS MER
18. Risk-based methods for reliability investments in electric power distribution systems
Sammanfattning : Society relies more and more on a continuous supply of electricity. However, while underinvestments in reliability lead to an unacceptable number of power interruptions, overinvestments result in too high costs for society. LÄS MER
19. A Microdata Analysis Approach to Transport Infrastructure Maintenance
Sammanfattning : Maintenance of transport infrastructure assets is widely advocated as the key in minimizing current and future costs of the transportation network. While effective maintenance decisions are often a result of engineering skills and practical knowledge, efficient decisions must also account for the net result over an asset's life-cycle. LÄS MER
20. Group-Sparse Regression : With Applications in Spectral Analysis and Audio Signal Processing
Sammanfattning : This doctorate thesis focuses on sparse regression, a statistical modeling tool for selecting valuable predictors in underdetermined linear models. By imposing different constraints on the structure of the variable vector in the regression problem, one obtains estimates which have sparse supports, i.e. LÄS MER