Sökning: "recommender systems"

Visar resultat 11 - 14 av 14 avhandlingar innehållade orden recommender systems.

  1. 11. Understanding Variability-Aware Analysis in Low-Maturity Variant-Rich Systems

    Författare :Mukelabai Mukelabai; Chalmers tekniska högskola; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

    Sammanfattning : Context : Software systems often exist in many variants to support varying stakeholder requirements, such as specific market segments or hardware constraints. Systems with many variants (a.k.a. LÄS MER

  3. 12. Contributions to Preventive Measures in Cyber Security

    Författare :Linus Karlsson; Institutionen för elektro- och informationsteknik; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

    Sammanfattning : Organizations and individuals maintain and use an ever increasing amount of computer systems, either deployed locally, or in the cloud.These systems often store and handle vast amounts of data, some of which is sensitive and should be kept private. LÄS MER

  4. 13. Online Dimensionality Reduction

    Författare :Kaito Ariu; Alexandre Proutiere; Mikael Johansson; Richard Combes; KTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

    Sammanfattning : In this thesis, we investigate online dimensionality reduction methods, wherethe algorithms learn by sequentially acquiring data. We focus on two specificalgorithm design problems in (i) recommender systems and (ii) heterogeneousclustering from binary user feedback. LÄS MER

  5. 14. Group-Sparse Regression : With Applications in Spectral Analysis and Audio Signal Processing

    Författare :Ted Kronvall; Statistical Signal Processing Group; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; sparse regression; group-sparsity; statistical modeling; regularization; hyperparameter-selection; spectral analysis; audio signal processing; classification; localization; multi-pitch estimation; chroma; convex optimization; ADMM; cyclic coordinate descent; proximal gradient;

    Sammanfattning : This doctorate thesis focuses on sparse regression, a statistical modeling tool for selecting valuable predictors in underdetermined linear models. By imposing different constraints on the structure of the variable vector in the regression problem, one obtains estimates which have sparse supports, i.e. LÄS MER