Blar i NTNU Open på forfatter "Yang, Zhirong"

Viser treff 21-26 av 26

    • A simple machine learning based framework for processing the inline inspection data of subsea pipelines 

      Liu, Zhenhui; Dahl, Sindre S.; Larsen, E. S.; Yang, Zhirong (Peer reviewed; Journal article, 2021)
      This paper presents a simple machine learning based framework for diagnosing the inline inspection data (ILI) of subsea pipelines. ILI data are obtained by intelligent pigging devices operating along subsea pipelines. The ...

    • Sparse factorization of square matrices with application to neural attention modeling 

      Khalitov, Ruslan; Yu, Tong; Cheng, Lei; Yang, Zhirong (Peer reviewed; Journal article, 2022)
      Square matrices appear in many machine learning problems and models. Optimization over a large square matrix is expensive in memory and in time. Therefore an economic approximation is needed. Conventional approximation ...

    • Stochastic Cluster Embedding 

      Yang, Zhirong; Chen, Yuwei; Sedov, Denis; Kaski, Samuel; Corander, Jukka (Peer reviewed; Journal article, 2023)
      Neighbor embedding (NE) aims to preserve pairwise similarities between data items and has been shown to yield an effective principle for data visualization. However, even the best existing NE methods such as stochastic ...

    • Stochastic Multiplicative Updates for Symmetric Nonnegative Matrix Factorization 

      Schlüter, Klara; Riege, Jon (Master thesis, 2021)
      Innen maskinlæring brukes symmetrisk ikkenegativ matrisefaktorisering (NMF) i forbindelse med clusteranalyse. NMF utføres ofte ved hjelp av algoritmer som tar i bruk multiplikative oppdateringer (MU). Disse har den fordelen ...

    • Stochastic Multiplicative Updates for Symmetric Nonnegative Matrix Factorization 

      Schlüter, Klara; Riege, Jon (Master thesis, 2021)
      Innen maskinlæring brukes symmetrisk ikkenegativ matrisefaktorisering (NMF) i forbindelse med clusteranalyse. NMF utføres ofte ved hjelp av algoritmer som tar i bruk multiplikative oppdateringer (MU). Disse har den fordelen ...

    • Word Embedding based on Low-Rank Doubly Stochastic Matrix Decomposition 

      Sedov, Denis; Yang, Zhirong (Chapter, 2018)
      Word embedding, which encodes words into vectors, is an important starting point in natural language processing and commonly used in many text-based machine learning tasks. However, in most current word embedding approaches, ...