• Pairwise local Fisher and naive Bayes: Improving two standard discriminants 

      Otneim, Håkon; Jullum, Martin; Tjøstheim, Dag Bjarne (Journal article; Peer reviewed, 2020)
      The Fisher discriminant is probably the best known likelihood discriminant for continuous data. Another benchmark discriminant is the naive Bayes, which is based on marginals only. In this paper we extend both discriminants ...
    • Some recent trends in embeddings of time series and dynamic networks 

      Tjøstheim, Dag Bjarne; Jullum, Martin; Løland, Anders (Journal article; Peer reviewed, 2023)
      We give a review of some recent developments in embeddings of time series and dynamic networks. We start out with traditional principal components and then look at extensions to dynamic factor models for time series. Unlike ...
    • Statistical Embedding: Beyond Principal Components 

      Tjøstheim, Dag Bjarne; Jullum, Martin; Løland, Anders (Journal article; Peer reviewed, 2023)
      There has been an intense recent activity in embedding of very high-dimensional and nonlinear data structures, much of it in the data science and machine learning literature. We survey this activity in four parts. In the ...