• 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 ...
    • Moreau envelope ADMM for decentralized weakly convex optimization 

      Mirzaeifard, Reza; Venkategowda, Naveen K. D.; Jung, Alexander; Werner, Stefan (Chapter, 2023)
      This paper proposes a proximal variant of the alternating direction method of multipliers (ADMM) for distributed optimization. Although the current versions of ADMM algorithm provide promising numerical results in producing ...
    • Robust Networked Federated Learning for Localization 

      Mirzaeifard, Reza; Venkategowda, Naveen K. D.; Werner, Anders Stefan (Chapter, 2023)
      This paper addresses the problem of localization, which is inherently non-convex and non-smooth in a federated setting where the data is distributed across a multitude of devices. Due to the decentralized nature of federated ...
    • Robust phase retrieval with non-convex penalties 

      Mirzaeifard, Reza; Dasanadoddi Venkategowda, Naveen Kumar; Werner, Anders Stefan (Journal article, 2023)
      This paper proposes an alternating direction method of multiplier (ADMM) based algorithm for solving the sparse robust phase retrieval with non-convex and non-smooth sparse penalties, such as minimax concave penalty (MCP). ...