Sökning: "High-dimensional data"

Visar resultat 21 - 25 av 114 avhandlingar innehållade orden High-dimensional data.

  1. 21. Algorithms and Methods for Robust Processing and Analysis of Mass Spectrometry Data

    Författare :Jonatan Eriksson; Avdelningen för Biomedicinsk teknik; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Mass Spectrometry; Algorithms; Signal Processing; Dynamic Programming; Biomarker discovery; High-dimensional data;

    Sammanfattning : Liquid chromatography-mass spectrometry (LC-MS) and mass spectrometry imaging (MSI) are two techniques that are routinely used to study proteins, peptides, and metabolites at a large scale. Thousands of biological compounds can be identified and quantified in a single experiment with LC-MS, but many studies fail to convert this data to a better understanding of disease biology. LÄS MER

  3. 22. The Word-Space Model: using distributional analysis to represent syntagmatic and paradigmatic relations between words in high-dimensional vector spaces

    Författare :Magnus Sahlgren; RISE; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

    Sammanfattning : .... LÄS MER

  4. 23. The Quest for Robust Model Selection Methods in Linear Regression

    Författare :Prakash Borpatra Gohain; Magnus Jansson; K.V.S Hari; KTH; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Model selection; information criterion; linear regression; sparsity; high dimensional; Electrical Engineering; Elektro- och systemteknik; Mathematical Statistics; Matematisk statistik;

    Sammanfattning : A fundamental requirement in data analysis is fitting the data to a model that can be used for the purpose of prediction and knowledge discovery. A typical and favored approach is using a linear model that explains the relationship between the response and the independent variables. LÄS MER

  5. 24. Breaking the Dimensionality Curse of Voronoi Tessellations

    Författare :Vladislav Polianskii; Florian T. Pokorny; Michael Bronstein; KTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; geometric methods; machine learning methods; Voronoi; Delaunay; high dimensional geometry; curse of dimensionality; monte carlo; Datalogi; Computer Science;

    Sammanfattning : Considering the broadness of the area of artificial intelligence, interpretations of the underlying methodologies can be commonly narrowed down to either a probabilistic or a geometric point of view. Such separation is especially prevalent in more classical "pre-neural-network" machine learning if one compares Bayesian modelling with more deterministic models like nearest neighbors. LÄS MER

  7. 25. Regression on high-dimensional predictor space : with application in chemometrics and microarray data

    Författare :Arief Gusnanto; Karolinska Institutet; Karolinska Institutet; []
    Nyckelord :Regression; near-infrared calibration; microarray; mixed model; logistic regression; random effects; variable selection; differential expression; mixture distribution;

    Sammanfattning : This thesis focuses on regression methodology for prediction and classification in situations where there are many predictors but limited number of observations. This situation is common in chemometrics and microarray data. LÄS MER