Blar i forfatter Artikler, rapporter og annet (informatikk) "Agarwal, Rohit"

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    • Aux-Drop: Handling Haphazard Inputs in Online Learning Using Auxiliary Dropouts 

      Agarwal, Rohit; Prasad, Dilip Kumar; Horsch, Ludwig Alexander; Gupta, Deepak Kumar (Journal article; Tidsskriftartikkel; Peer reviewed, 2023)
      Many real-world applications based on online learning produce streaming data that is haphazard in nature, i.e., contains missing features, features becoming obsolete in time, the appearance of new features at later points in time and a lack of clarity on the total number of input features. These challenges make it hard to build a learnable system for such applications, and almost no work exists in ...

    • Auxiliary Network: Scalable and agile online learning for dynamic system with inconsistently available inputs 

      Agarwal, Rohit; Agarwal, Krishna; Horsch, Alexander; Prasad, Dilip K. (Journal article; Tidsskriftartikkel, 2022-04-13)
      Streaming classification methods assume the number of input features is fixed and always received. But in many real-world scenarios, some features are reliable while others are unreliable or inconsistent. We propose a novel online deep learning-based model called Auxiliary Network (Aux-Net), which is scalable and agile and can handle any number of inputs at each time instance. The Aux-Net model is ...

    • Mabnet: Master Assistant Buddy Network With Hybrid Learning for Image Retrieval 

      Agarwal, Rohit; Das, Gyanendra; Aggarwal, Saksham; Horsch, Ludwig Alexander; Prasad, Dilip Kumar (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-05-05)
      Image retrieval has garnered a growing interest in recent times. The current approaches are either supervised or self-supervised. These methods do not exploit the benefits of hybrid learning using both supervision and self-supervision. We present a novel Master Assistant Buddy Network (MAB-Net) for image retrieval which incorporates both the learning mechanisms. MABNet consists of master and assistant ...