Sökning: "Machine Learning"

Visar resultat 1 - 5 av 661 avhandlingar innehållade orden Machine Learning.

  1. 1. Approaches to Interactive Online Machine Learning

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

    Sammanfattning : 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. LÄS MER

  2. 2. Interactive Online Machine Learning

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

    Sammanfattning : 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. LÄS MER

  3. 3. Modularization of the Learning Architecture : Supporting Learning Theories by Learning Technologies

    Författare :Fredrik Paulsson; Yngve Sundblad; Miguel Angel-Cecilia; KTH; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Computer Science; Technology Enhanced Learning; e-learning; Semantic Web; Service Orientation; Learning Object; Virtual Learning Environment; Computer science; Datavetenskap;

    Sammanfattning : This thesis explores the role of modularity for achieving a better adaptation of learning technology to pedagogical requirements. In order to examine the interrelations that occur between pedagogy and computer science, a theoretical framework rooted in both fields is applied. LÄS MER

  4. 4. Protein Model Quality Assessment : A Machine Learning Approach

    Författare :Karolis Uziela; Arne Elofsson; Liam McGuffin; Stockholms universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Protein Model Quality Assessment; structural bioinformatics; machine learning; deep learning; support vector machine; proq; Artificial Neural Network; protein structure prediction; Biochemistry towards Bioinformatics; biokemi med inriktning mot bioinformatik;

    Sammanfattning : Many protein structure prediction programs exist and they can efficiently generate a number of protein models of a varying quality. One of the problems is that it is difficult to know which model is the best one for a given target sequence. Selecting the best model is one of the major tasks of Model Quality Assessment Programs (MQAPs). LÄS MER

  5. 5. Robust machine learning methods

    Författare :Muhammad Osama; Dave Zachariah; Thomas B. Schön; Visa Koivunen; Uppsala universitet; []
    Nyckelord :ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; artificial intelligence; machine learning; risk minimization; data corruption; decision policy; conformal methods; data from contexts; online learning; spice; robust; causal inference; point process; localization; distribution uncertainty; treatment rules; quantile treatment; predicting count data; Electrical Engineering with specialization in Signal Processing; Elektroteknik med inriktning mot signalbehandling;

    Sammanfattning : We are surrounded by data in our daily lives. The rent of our houses, the amount of electricity units consumed, the prices of different products at a supermarket, the daily temperature, our medicine prescriptions, our internet search history are all different forms of data. Data can be used in a wide range of applications. LÄS MER