Essays about: "Erik Rosvall"

Found 4 essays containing the words Erik Rosvall.

  1. 1. Feature Selection for Microarray Data via Stochastic Approximation

    University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

    Author : Erik Rosvall; [2024-03-18]
    Keywords : feature selection; feature ranking; microarray data; stochastic approximation; Barzilai and Borwein method; Machine Learning; AI;

    Abstract : This thesis explores the challenge of feature selection (FS) in machine learning, which involves reducing the dimensionality of data. The selection of a relevant subset of features from a larger pool has demonstrated its effectiveness in enhancing the performance of various machine learning algorithms. READ MORE

  2. 2. Comparison of sequence classification techniques with BERT for named entity recognition

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Erik Rosvall; [2019]
    Keywords : ;

    Abstract : This thesis takes its starting point from the recent advances in Natural Language Processing being developed upon the Transformer model. One of the significant developments recently was the release of a deep bidirectional encoder called BERT that broke several state of the art results at its release. READ MORE

  3. 3. Extreme Kernel Machine

    University essay from KTH/Skolan för teknikvetenskap (SCI)

    Author : Viktor Karlsson; Erik Rosvall; [2017]
    Keywords : ;

    Abstract : The purpose of this report is to examine the combinationof an Extreme Learning Machine (ELM) with the KernelMethod. Kernels lies at the core of Support Vector Machines successin classifying non-linearly separable datasets. The hypothesisis that by combining ELM with a kernel we will utilize featuresin the ELM-space otherwise unused. READ MORE

  4. 4. Extreme Kernel Machine

    University essay from KTH/Skolan för teknikvetenskap (SCI)

    Author : Viktor Karlsson; Erik Rosvall; [2017]
    Keywords : ;

    Abstract : The purpose of this report is to examine the combination of an Extreme Learning Machine (ELM) with the Kernel Method . Kernels lies at the core of Support Vector Machines success in classifying non-linearly separable datasets. The hypothesis is that by combining ELM with a kernel we will utilize features in the ELM-space otherwise unused. READ MORE