Sökning: "Learning over networks"
Visar resultat 1 - 5 av 136 avhandlingar innehållade orden Learning over networks.
1. Generalization under Model Mismatch and Distributed Learning
Sammanfattning : Machine learning models are typically configured by minimizing the training error over a given training dataset. On the other hand, the main objective is to obtain models that can generalize, i.e., perform well on data unseen during training. LÄS MER
2. Bayesian structure learning in graphical models
Sammanfattning : This thesis consists of two papers studying structure learning in probabilistic graphical models for both undirected graphs anddirected acyclic graphs (DAGs).Paper A, presents a novel family of graph theoretical algorithms, called the junction tree expanders, that incrementally construct junction trees for decomposable graphs. LÄS MER
3. Learning to Control the Cloud
Sammanfattning : With the growth of the cloud industry in recent years, the energy consumption of the underlying infrastructure is a major concern.The need for energy efficient resource management and control in the cloud becomes increasingly important as one part of the solution, where the other is to reduce the energy consumption of the hardware itself. LÄS MER
4. Learning time-varying interaction networks
Sammanfattning : Most biological systems consist of several subcomponents whichinteract with each other. These interactions govern the overall behaviourof the system; and in turn vary over time and in response to internaland external stress during the course of an experiment. LÄS MER
5. Structured Representations for Explainable Deep Learning
Sammanfattning : Deep learning has revolutionized scientific research and is being used to take decisions in increasingly complex scenarios. With growing power comes a growing demand for transparency and interpretability. The field of Explainable AI aims to provide explanations for the predictions of AI systems. LÄS MER