16 citations · 37 across the 13 of their papers we have counts for
3 papers · 1 filter
AntMan: Sparse Low-Rank Compression to Accelerate RNN inference
Samyam Rajbhandari, Harsh Shrivastava, Yuxiong He
Wide adoption of complex RNN based models is hindered by their inference performance, cost and memory requirements. To address this issue, we develop AntMan, combining structured s…
Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification
Harsh Shrivastava, Eugene Bart, Bob Price +3
We propose a new approach, called cooperative neural networks (CoNN), which uses a set of cooperatively trained neural networks to capture latent representations that exploit prior…
GLAD: Learning Sparse Graph Recovery
Harsh Shrivastava, Xinshi Chen, Binghong Chen +4
Recovering sparse conditional independence graphs from data is a fundamental problem in machine learning with wide applications. A popular formulation of the problem is an …