Sökning: "network representations"
Visar resultat 16 - 20 av 86 avhandlingar innehållade orden network representations.
16. Modeling Organizational Dynamics : Distributions, Networks, Sequences and Mechanisms
Sammanfattning : The study of how social organizations work, change and develop is central to sociology and to our understanding of the social world and its transformations. At the same time, the underlying principles of organizational dynamics are extremely difficult to investigate. LÄS MER
17. Low and Medium Level Vision Using Channel Representations
Sammanfattning : This thesis introduces and explores a new type of representation for low and medium level vision operations called channel representation. The channel representation is a more general way to represent information than e.g. as numerical values, since it allows incorporation of uncertainty, and simultaneous representation of several hypotheses. LÄS MER
18. Transfer Learning using low-dimensional Representations in Reinforcement Learning
Sammanfattning : Successful learning of behaviors in Reinforcement Learning (RL) are often learned tabula rasa, requiring many observations and interactions in the environment. Performing this outside of a simulator, in the real world, often becomes infeasible due to the large amount of interactions needed. LÄS MER
19. Methods for Network Optimization and Parallel Derivative-free Optimization
Sammanfattning : This thesis is divided into two parts that each is concerned with a specific problem.The problem under consideration in the first part is to find suitable graph representations, abstractions, cost measures and algorithms for calculating placements of unmanned aerial vehicles (UAVs) such that they can keep one or several static targets under constant surveillance. LÄS MER
20. Towards Better Representation Learning in the Absence of Sufficient Supervision
Sammanfattning : We focus on the problem of learning representations from data in the situation where we do not have access to sufficient supervision such as labels or feature values. This situation can be present in many real-world machine learning tasks. We approach this problem from different perspectives summarized as follows. LÄS MER