Sökning: "Learning regions"
Visar resultat 41 - 45 av 188 avhandlingar innehållade orden Learning regions.
41. Efficient and Trustworthy Artificial Intelligence for Critical Robotic Systems
Sammanfattning : Critical robotic systems are systems whose functioning is critical to both ensuring the accomplishment of a given mission and preventing the endangerment of life and the surrounding environment. These critical aspects can be formally captured by convergence, in the sense that the system's state goes to a desired region of the statespace, and safety, in the sense that the system's state avoids unsafe regions of the statespace. LÄS MER
42. Nonconformity Measures and Ensemble Strategies : An Analysis of Conformal Predictor Efficiency and Validity
Sammanfattning : Conformal predictors are a family of predictive models that associate with each of their predictions a measure of confidence, enabling them to provide quantitative information about their own trustworthiness. In risk-laden machine learning applications, where bad predictions may lead to economic loss, personal injury, or worse, such inherent quality control appears highly beneficial, if not required. LÄS MER
43. Developing transnational industrial platforms: – the strategic conception of the Öresund region
Sammanfattning : This book is particularly concerned with examining the creation of the Öresund region, a process that represents the internationalization and geopolitical changes in the world, where new industrial regions emerge in competition for growth and wealth. The emerging Öresund region is a new type of industrial region – a transnational region that is difficult to analyze in a traditional way, for example, by a structural economic analysis. LÄS MER
44. Integrating multi-omics for type 2 diabetes : Data science and big data towards personalized medicine
Sammanfattning : Type 2 diabetes (T2D) is a complex metabolic disease characterized by multi-tissue insulin resistance and failure of the pancreatic β-cells to secrete sufficient amounts of insulin. Cells recruit transcription factors (TF) to specific genomic loci to regulate gene expression that consequently affects the protein and metabolite abundancies. LÄS MER
45. Multi-LSTM Acceleration and CNN Fault Tolerance
Sammanfattning : This thesis addresses the following two problems related to the field of Machine Learning: the acceleration of multiple Long Short Term Memory (LSTM) models on FPGAs and the fault tolerance of compressed Convolutional Neural Networks (CNN). LSTMs represent an effective solution to capture long-term dependencies in sequential data, like sentences in Natural Language Processing applications, video frames in Scene Labeling tasks or temporal series in Time Series Forecasting. LÄS MER
