Search for dissertations about: "machine learning algorithm"

Showing result 1 - 5 of 217 swedish dissertations containing the words machine learning algorithm.

2. 1. Approaches to Interactive Online Machine Learning

   Author : Agnes Tegen; Paul Davidsson; Jan A. Persson; Henrik Boström; Malmö universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Machine Learning; Interactive Machine Learning; Online Learning; Active Learning; Machine Teaching;

   Abstract : With the Internet of Things paradigm, the data generated by the rapidly increasing number of connected devices lead to new possibilities, such as using machine learning for activity recognition in smart environments. However, it also introduces several challenges. READ MORE

4. 2. Interactive Online Machine Learning

   Author : Agnes Tegen; Paul Davidsson; Jan A. Persson; Georg Krempl; Malmö universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Interactive Machine Learning; Active Learning; Machine Teaching; Online Learning;

   Abstract : With the Internet of Things paradigm, the data generated by the rapidly increasing number of connected devices lead to new possibilities, such as using machine learning for activity recognition in smart environments. However, it also introduces several challenges. The sensors of different devices might be mobile and of different types, i.e. READ MORE

5. 3. Energy Efficiency in Machine Learning : Approaches to Sustainable Data Stream Mining

   Author : Eva García Martín; Håkan Grahn; Veselka Boeva; Emiliano Casalicchio; Jesse Read; Blekinge Tekniska Högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; machine learning; energy efficiency; data stream mining; green machine learning; edge computing; Computer Science; Datavetenskap;

   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

6. 4. On Deep Machine Learning Based Techniques for Electric Power Systems

   Author : Ebrahim Balouji; Chalmers tekniska högskola; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Deep Learning; Cable faults; phase locked loop; Flicker; Harmonics and Interharmonics; Reinforcement learning; Voltage Dip; Active Power filter; Machine Learning; Voltage fluctuation; Partial Discharges;

   Abstract : This thesis provides deep machine learning-based solutions to real-time mitigation of power quality disturbances such as flicker, voltage dips, frequency deviations, harmonics, and interharmonics using active power filters (APF). In an APF the processing delays reduce the performance when the disturbance to be mitigated is tima varying. READ MORE

7. 5. Reliable and Efficient Distributed Machine Learning

   Author : Hao Chen; Ming Xiao; Mikael Skoglund; Yan Zhang; KTH; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Distributed machine learning; federated learning; communication efficiency; decentralized optimization; Electrical Engineering; Elektro- och systemteknik;

   Abstract : With the ever-increasing penetration and proliferation of various smart Internet of Things (IoT) applications, machine learning (ML) is envisioned to be a key technique for big-data-driven modelling and analysis. Since massive data generated from these IoT devices are commonly collected and stored in a distributed manner, ML at the networks, e.g. READ MORE