no code implementations • EMNLP 2020 • Raul Puri, Ryan Spring, Mostofa Patwary, Mohammad Shoeybi, Bryan Catanzaro
On the SQuAD1. 1 question answering task, we achieve higher accuracy using solely synthetic questions and answers than when using the SQuAD1. 1 training set questions alone.
1 code implementation • 1 Feb 2019 • Ryan Spring, Anastasios Kyrillidis, Vijai Mohan, Anshumali Shrivastava
The problem is becoming more severe as deep learning models continue to grow larger in order to learn from complex, large-scale datasets.
1 code implementation • ICML 2018 • Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, baraniuk
We demonstrate that MISSION accurately and efficiently performs feature selection on real-world, large-scale datasets with billions of dimensions.
1 code implementation • 12 Jun 2018 • Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, Richard G. Baraniuk
We demonstrate that MISSION accurately and efficiently performs feature selection on real-world, large-scale datasets with billions of dimensions.
1 code implementation • 15 Mar 2017 • Ryan Spring, Anshumali Shrivastava
We propose a new sampling scheme and an unbiased estimator that estimates the partition function accurately in sub-linear time.
no code implementations • 26 Feb 2016 • Ryan Spring, Anshumali Shrivastava
A unique property of the proposed hashing based back-propagation is that the updates are always sparse.