11 citations · 43 across the 9 of their papers we have counts for
3 papers · 1 filter
On Generalization of Adaptive Methods for Over-parameterized Linear Regression
Vatsal Shah, Soumya Basu, Anastasios Kyrillidis +1
Over-parameterization and adaptive methods have played a crucial role in the success of deep learning in the last decade. The widespread use of over-parameterization has forced us…
Robust Estimation of Tree Structured Ising Models
Ashish Katiyar, Vatsal Shah, Constantine Caramanis
We consider the task of learning Ising models when the signs of different random variables are flipped independently with possibly unequal, unknown probabilities. In this paper, we…
Choosing the Sample with Lowest Loss makes SGD Robust
Vatsal Shah, Xiaoxia Wu, Sujay Sanghavi
The presence of outliers can potentially significantly skew the parameters of machine learning models trained via stochastic gradient descent (SGD). In this paper we propose a simp…