Sökning: "sparse learning"

Visar resultat 6 - 10 av 67 avhandlingar innehållade orden sparse learning.

  1. 6. Interpretable machine learning models for predicting with missing values

    Författare :Lena Stempfle; Chalmers tekniska högskola; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; missing values; Machine learning; healthcare; interpretable machine learning;

    Sammanfattning : Machine learning models are often used in situations where model inputs are missing either during training or at the time of prediction. If missing values are not handled appropriately, they can lead to increased bias or to models that are not applicable in practice without imputing the values of the unobserved variables. LÄS MER

  3. 7. Learning in visual art practice

    Författare :Ann-Mari Edström; Pedagogik; []
    Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; self-directed learning; studio art; phenomenography; higher education; contextual analysis; visual art practice; Autonomy; artistic development;

    Sammanfattning : The object of research in this thesis is learning within the context of a practice-based Master of Fine Arts program in visual art in Sweden. Research on learning in visual art practice within higher education is sparse, and we know little of the students’ learning processes. LÄS MER

  4. 8. Sparse Modeling of Grouped Line Spectra

    Författare :Ted Kronvall; Statistical Signal Processing Group; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; line spectra; parameter estimation; convex optimization; group-sparsity; block-sparsity; dictionary learning; ADMM; adaptive penalty; total variation; multi-pitch estimation; chroma; audio processing; TDOA; near-field localization; amplitude modulation;

    Sammanfattning : This licentiate thesis focuses on clustered parametric models for estimation of line spectra, when the spectral content of a signal source is assumed to exhibit some form of grouping. Different from previous parametric approaches, which generally require explicit knowledge of the model orders, this thesis exploits sparse modeling, where the orders are implicitly chosen. LÄS MER

  5. 9. Scalable Machine Learning through Approximation and Distributed Computing

    Författare :Theodore Vasiloudis; Anders Holst; Henrik Boström; Seif Haridi; Daniel Gillblad; Indre Žliobaitė; KTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Online Learning; Distributed Computing; Graph Similarity; Decision Trees; Gradient Boosting;

    Sammanfattning : Machine learning algorithms are now being deployed in practically all areas of our lives. Part of this success can be attributed to the ability to learn complex representations from massive datasets. LÄS MER

  7. 10. Data-Driven Approaches for Sparse Reflectance Modeling and Acquisition

    Författare :Tanaboon Tongbuasirilai; Jonas Unger; Ehsan Miandji; Jakob Wenzel; Linköpings universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; BRDF; Reflectance modeling; Sparse representation; Compressed sensing; Factorization;

    Sammanfattning : Photo-realistic rendering and predictive image synthesis are becoming increasingly important and utilized in many application areas ranging from production of visual effects and product visualization to digital design and the generation of synthetic data for visual machine learning applications. Many essential components of the realistic image synthesis pipelines have been developed tremendously over the last decades. LÄS MER