24 citations · 29 across the 2 of their papers we have counts for
3 papers
cs.CL2020
Training Question Answering Models From Synthetic Data
Raul Puri, Ryan Spring, Mostofa Patwary +2
Question and answer generation is a data augmentation method that aims to improve question answering (QA) models given the limited amount of human labeled data. However, a consider…
cs.LG2019★ 5 cited
Compressing Gradient Optimizers via Count-Sketches
Ryan Spring, Anastasios Kyrillidis, Vijai Mohan +1
Many popular first-order optimization methods (e.g., Momentum, AdaGrad, Adam) accelerate the convergence rate of deep learning models. However, these algorithms require auxiliary p…
stat.ML2017★ 24 cited
A New Unbiased and Efficient Class of LSH-Based Samplers and Estimators for Partition Function Computation in Log-Linear Models
Ryan Spring, Anshumali Shrivastava
Log-linear models are arguably the most successful class of graphical models for large-scale applications because of their simplicity and tractability. Learning and inference with…