Search for dissertations about: "machine learning in testing"

Showing result 1 - 5 of 51 swedish dissertations containing the words machine learning in testing.

  2. 1. Statistical Feature Selection : With Applications in Life Science

    Author : Roland Nilsson; Jesper Tegnér; Johan Björkegren; Sepp Hochreiter; Linköpings universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Machine learning; supervised learning; classification; dimemsionality reduction; multiple testing; gene expression; microarray; cancer; Bioinformatics; Bioinformatik;

    Abstract : The sequencing of the human genome has changed life science research in many ways. Novel measurement technologies such as microarray expression analysis, genome-wide SNP typing and mass spectrometry are now producing experimental data of extremely high dimensions. READ MORE

  4. 2. Learning-based Software Testing using Symbolic Constraint Solving Methods

    Author : Fei Niu; Karl Meinke; Reiner Hähnle; KTH; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Testing; Machine learning; Symbolic constraint solving; Model checking;

    Abstract : Software testing remains one of the most important but expensive approaches to ensure high-quality software today. In order to reduce the cost of testing, over the last several decades, various techniques such as formal verification and inductive learning have been used for test automation in previous research. READ MORE

  5. 3. Learning-based Testing for Automotive Embedded Systems : A requirements modeling and Fault injection study

    Author : Hojat Khosrowjerdi; Karl Meinke; Dilian Gurov; Cristina Seceleanu; KTH; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Machine learning; fault injection; requirements testing; embedded systems; model checking; automotive software; requirements modeling; Computer Science; Datalogi;

    Abstract : This thesis concerns applications of learning-based testing (LBT) in the automotive domain. In this domain, LBT is an attractive testing solution, since it offers a highly automated technology to conduct safety critical requirements testing based on machine learning. READ MORE

  6. 4. Machine learning for anomaly detection in edge clouds

    Author : Javad Forough; Erik Elmroth; Monowar H. Bhuyan; Shahid Raza; Umeå universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Edge Clouds; Anomaly Detection; Machine Learning;

    Abstract : Edge clouds have emerged as an essential architecture, revolutionizing data processing and analysis by bringing computational capabilities closer to data sources and end-users at the edge of the network. Anomaly detection is crucial in these settings to maintain the reliability and security of edge-based systems and applications despite limited computational resources. READ MORE

  7. 5. A study of wireless communications with reinforcement learning

    Author : Wanlu Lei; Ming Xiao; Chenguang Lu; Mikael Skoglund; Geoffrey Ye Li; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Reinforcement learning; wireless communications; decentralized learning; beam tracking; machine learning; Förstärkningsinlärning; trådlös kommunikation; decentrali- serad inlärning; strålspårning i mmvåg; maskininlärning; Electrical Engineering; Elektro- och systemteknik;

    Abstract :  The explosive proliferation of mobile users and wireless data traffic in recent years pose imminent challenges upon wireless system design. The trendfor wireless communications becoming more complicated, decentralized andintelligent is inevitable. READ MORE