25 citations · 25 across the 2 of their papers we have counts for
2 papers
cs.LG2020★ 25 cited
Hierarchical Quantized Autoencoders
Will Williams, Sam Ringer, Tom Ash +3
Despite progress in training neural networks for lossy image compression, current approaches fail to maintain both perceptual quality and abstract features at very low bitrates. En…
cs.DS2018
Leveraging Sparsity to Speed Up Polynomial Feature Expansions of CSR Matrices Using -Simplex Numbers
Andrew Nystrom, John Hughes
An algorithm is provided for performing polynomial feature expansions that both operates on and produces compressed sparse row (CSR) matrices. Previously, no such algorithm existed…