2 papers
cs.LG2025
Balancing Sparse RNNs with Hyperparameterization Benefiting Meta-Learning
Quincy Hershey, Randy Paffenroth
This paper develops alternative hyperparameters for specifying sparse Recurrent Neural Networks (RNNs). These hyperparameters allow for varying sparsity within the trainable weight…
cs.LG2024
Rethinking the Relationship between Recurrent and Non-Recurrent Neural Networks: A Study in Sparsity
Quincy Hershey, Randy Paffenroth, Harsh Pathak +1
Neural networks (NN) can be divided into two broad categories, recurrent and non-recurrent. Both types of neural networks are popular and extensively studied, but they are often tr…