3 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…
cs.LG2023
ChemVise: Maximizing Out-of-Distribution Chemical Detection with the Novel Application of Zero-Shot Learning
Alexander M. Moore, Randy C. Paffenroth, Ken T. Ngo +1
Accurate chemical sensors are vital in medical, military, and home safety applications. Training machine learning models to be accurate on real world chemical sensor data requires…