Blar i NTNU Open på forfatter "Kumar Dasanadoddi Venkategowda, Naveen"

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    • Communication-efficient and privacy-aware distributed LMS algorithm 

      Gogineni, Vinay Chakravarthi; Moradi, Ashkan; Kumar Dasanadoddi Venkategowda, Naveen; Werner, Stefan (Chapter, 2022)
      This paper presents a private-partial distributed least mean square (PP-DLMS) algorithm that offers energy efficiency while preserving privacy and is suitable for applications with limited resources and strict security ...

    • Distributed Learning over Networks with Non-Smooth Regularizers and Feature Partitioning 

      Gratton, Cristiano; Kumar Dasanadoddi Venkategowda, Naveen; Arablouei, Reza; Werner, Stefan (Chapter, 2021)
      We develop a new algorithm for distributed learning with non-smooth regularizers and feature partitioning. To this end, we transform the underlying optimization problem into a suitable dual form and solve it using the ...

    • Distributed quantile regression with non-convex sparse penalties 

      Mirzaeifard, Reza; Gogineni, Vinay Chakravarthi; Kumar Dasanadoddi Venkategowda, Naveen; Werner, Anders Stefan (Peer reviewed; Journal article, 2023)
      The surge in data generated by IoT sensors has increased the need for scalable and efficient data analysis methods, particularly for robust algorithms like quantile regression, which can be tailored to meet a variety of ...

    • Privacy-Preserved Distributed Learning With Zeroth-Order Optimization 

      Gratton, Cristiano; Kumar Dasanadoddi Venkategowda, Naveen; Arablouei, Reza; Werner, Stefan (Peer reviewed; Journal article, 2022)
      We develop a privacy-preserving distributed algorithm to minimize a regularized empirical risk function when the first-order information is not available and data is distributed over a multi-agent network. We employ a ...

    • Quickest Detection of Stochastic False Data Injection Attacks with Unknown Parameters 

      D'Avila Barros, Bettina; Kumar Dasanadoddi Venkategowda, Naveen; Werner, Stefan (Chapter, 2021)
      This paper considers a multivariate quickest detection problem with false data injection (FDI) attacks in internet of things (IoT) systems. We derive a sequential generalized likelihood ratio test (GLRT) for zero-mean ...