Sökning: "Hyper focus"
Visar resultat 1 - 5 av 20 avhandlingar innehållade orden Hyper focus.
1. Three or Four Ir/relevant Stories : Art and Hyper-Politics
Sammanfattning : This book documents and reflects on three artistic projects and their processes. As a “marginalia” to the projects I also presents arguments, stories and ir/ relevant discourses. What I call marginalia extends to aspects of a historical backdrop of these three projects and the stories behind them. LÄS MER
2. Reliability Assessment and Probabilistic Optimization in Structural Design
Sammanfattning : Research in the field of reliability based design is mainly focused on two sub-areas: The computation of the probability of failure and its integration in the reliability based design optimization (RBDO) loop. Four papers are presented in this work, representing a contribution to both sub-areas. LÄS MER
3. Det ekte, det gode og det coole : Södra teatern og den dialogiske formasjonen av mangfoldsdiskursen
Sammanfattning : The thesis analyses the continuously changing discourse of cultural diversity. The focus of this study is the ways in which this discourse is shaped within contemporary Swedish cultural politics in general, and how it unfolds and further changes through the specific activities performed by a cultural institution in Stockholm – Södra teatern. LÄS MER
4. Energy Efficiency in Machine Learning : Approaches to Sustainable Data Stream Mining
Sammanfattning : Energy efficiency in machine learning explores how to build machine learning algorithms and models with low computational and power requirements. Although energy consumption is starting to gain interest in the field of machine learning, still the majority of solutions focus on obtaining the highest predictive accuracy, without a clear focus on sustainability. LÄS MER
5. Evolving intelligence : Overcoming challenges for Evolutionary Deep Learning
Sammanfattning : Deep Learning (DL) has achieved remarkable results in both academic and industrial fields over the last few years. However, DL models are often hard to design and require proper selection of features and tuning of hyper-parameters to achieve high performance. These selections are tedious for human experts and require substantial time and resources. LÄS MER