3 citations · 4 across the 2 of their papers we have counts for
2 papers
stat.ML2022★ 1 cited
A novel nonconvex, smooth-at-origin penalty for statistical learning
Majnu John, Sujit Vettam, Yihren Wu
Nonconvex penalties are utilized for regularization in high-dimensional statistical learning algorithms primarily because they yield unbiased or nearly unbiased estimators for the…
stat.ML2019★ 3 cited
Regularized deep learning with nonconvex penalties
Sujit Vettam, Majnu John
Regularization methods are often employed in deep learning neural networks (DNNs) to prevent overfitting. For penalty based DNN regularization methods, convex penalties are typical…