• Model-based hyperparameter optimization 

    Crouther, Paul (2023-05-29)
    The primary goal of this work is to propose a methodology for discovering hyperparameters. Hyperparameters aid systems in convergence when well-tuned and handcrafted. However, to this end, poorly chosen hyperparameters leave practitioners in limbo, ...
  • Towards better understanding and improving optimization in recurrent neural networks 

    Kanuparthi, Bhargav (2020-12-16)
    Recurrent neural networks (RNN) are known for their notorious exploding and vanishing gradient problem (EVGP). This problem becomes more evident in tasks where the information needed to correctly solve them exist over long time scales, because it ...