83 citations · 87 across the 3 of their papers we have counts for
5 papers · 1 filter
MANGO: A Python Library for Parallel Hyperparameter Tuning
Sandeep Singh Sandha, Mohit Aggarwal, Igor Fedorov +1
Tuning hyperparameters for machine learning algorithms is a tedious task, one that is typically done manually. To enable automated hyperparameter tuning, recent works have started…
Pushing the limits of RNN Compression
Urmish Thakker, Igor Fedorov, Jesse Beu +4
Recurrent Neural Networks (RNN) can be difficult to deploy on resource constrained devices due to their size. As a result, there is a need for compression techniques that can signi…
Compressing RNNs for IoT devices by 15-38x using Kronecker Products
Urmish Thakker, Jesse Beu, Dibakar Gope +4
Recurrent Neural Networks (RNN) can be difficult to deploy on resource constrained devices due to their size.As a result, there is a need for compression techniques that can signif…
SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers
Igor Fedorov, Ryan P. Adams, Matthew Mattina +1
The vast majority of processors in the world are actually microcontroller units (MCUs), which find widespread use performing simple control tasks in applications ranging from autom…
Re-Weighted Learning for Sparsifying Deep Neural Networks
Igor Fedorov, Bhaskar D. Rao
This paper addresses the topic of sparsifying deep neural networks (DNN's). While DNN's are powerful models that achieve state-of-the-art performance on a large number of tasks, th…