2 citations · 3 across the 8 of their papers we have counts for
5 papers · 1 filter
Label-Free Reinforcement Learning via Cross-Model Entropy
Matt Gorbett, Hossein Shirazi
Post-training large language models with reinforcement learning is bottlenecked by the reward signal. Existing approaches require either ground-truth verifiable rewards, restrictin…
Tiled Bit Networks: Sub-Bit Neural Network Compression Through Reuse of Learnable Binary Vectors
Matt Gorbett, Hossein Shirazi, Indrakshi Ray
Binary Neural Networks (BNNs) enable efficient deep learning by saving on storage and computational costs. However, as the size of neural networks continues to grow, meeting comput…
Cross-Silo Federated Learning Across Divergent Domains with Iterative Parameter Alignment
Matt Gorbett, Hossein Shirazi, Indrakshi Ray
Learning from the collective knowledge of data dispersed across private sources can provide neural networks with enhanced generalization capabilities. Federated learning, a method…
Sparse Binary Transformers for Multivariate Time Series Modeling
Matt Gorbett, Hossein Shirazi, Indrakshi Ray
Compressed Neural Networks have the potential to enable deep learning across new applications and smaller computational environments. However, understanding the range of learning t…
Randomly Initialized Subnetworks with Iterative Weight Recycling
Matt Gorbett, Darrell Whitley
The Multi-Prize Lottery Ticket Hypothesis posits that randomly initialized neural networks contain several subnetworks that achieve comparable accuracy to fully trained models of t…