62 citations · 63 across the 2 of their papers we have counts for
3 papers
Overcomplete Frame Thresholding for Acoustic Scene Analysis
Romain Cosentino, Randall Balestriero, Richard Baraniuk +1
In this work, we derive a generic overcomplete frame thresholding scheme based on risk minimization. Overcomplete frames being favored for analysis tasks such as classification, re…
Training Neural Networks Without Gradients: A Scalable ADMM Approach
Gavin Taylor, Ryan Burmeister, Zheng Xu +3
With the growing importance of large network models and enormous training datasets, GPUs have become increasingly necessary to train neural networks. This is largely because conven…
A Probabilistic Theory of Deep Learning
Ankit B. Patel, Tan Nguyen, Richard G. Baraniuk
A grand challenge in machine learning is the development of computational algorithms that match or outperform humans in perceptual inference tasks that are complicated by nuisance…