357 citations · 2.8k across the 94 of their papers we have counts for
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stat.ML2016★ 87 cited
Parallelizing Stochastic Gradient Descent for Least Squares Regression: mini-batching, averaging, and model misspecification
Prateek Jain, Sham M. Kakade, Rahul Kidambi +2
This work characterizes the benefits of averaging schemes widely used in conjunction with stochastic gradient descent (SGD). In particular, this work provides a sharp analysis of:…
stat.ML2016★ 10 cited
Structured Sparse Regression via Greedy Hard-Thresholding
Prateek Jain, Nikhil Rao, Inderjit Dhillon
Several learning applications require solving high-dimensional regression problems where the relevant features belong to a small number of (overlapping) groups. For very large data…