3 citations · 5 across the 2 of their papers we have counts for
4 papers
Echo State Speech Recognition
Harsh Shrivastava, Ankush Garg, Yuan Cao +2
We propose automatic speech recognition (ASR) models inspired by echo state network (ESN), in which a subset of recurrent neural networks (RNN) layers in the models are randomly in…
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 …