Search for dissertations about: "data mining machine learning"
Showing result 1 - 5 of 59 swedish dissertations containing the words data mining machine learning.
-
1. Energy Efficiency in Machine Learning : Approaches to Sustainable Data Stream Mining
Abstract : 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. READ MORE
-
2. How can data science contribute to a greener world? : an exploration featuring machine learning and data mining for environmental facilities and energy end users
Abstract : Human society has taken many measures to address environmental issues. For example, deploying wastewater treatment plants (WWTPs) to alleviate water pollution and the shortage of usable water; using waste-to-energy (WtE) plants to recover energy from the waste and reduce its environmental impact. READ MORE
-
3. Mining Speech Sounds : Machine Learning Methods for Automatic Speech Recognition and Analysis
Abstract : This thesis collects studies on machine learning methods applied to speech technology and speech research problems. The six research papers included in this thesis are organised in three main areas. The first group of studies were carried out within the European project Synface. READ MORE
-
4. Learning predictive models from graph data using pattern mining
Abstract : Learning from graphs has become a popular research area due to the ubiquity of graph data representing web pages, molecules, social networks, protein interaction networks etc. However, standard graph learning approaches are often challenged by the computational cost involved in the learning process, due to the richness of the representation. READ MORE
-
5. Extraction and Energy Efficient Processing of Streaming Data
Abstract : The interest in machine learning algorithms is increasing, in parallel with the advancements in hardware and software required to mine large-scale datasets. Machine learning algorithms account for a significant amount of energy consumed in data centers, which impacts the global energy consumption. READ MORE