22 citations
3 papers
stat.ME2021★ 4 cited
Tree-based Node Aggregation in Sparse Graphical Models
Ines Wilms, Jacob Bien
High-dimensional graphical models are often estimated using regularization that is aimed at reducing the number of edges in a network. In this work, we show how even simpler networ…
cs.LG2018★ 22 cited
Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced
Simon S. Du, Wei Hu, Jason D. Lee
We study the implicit regularization imposed by gradient descent for learning multi-layer homogeneous functions including feed-forward fully connected and convolutional deep neural…
stat.ME2018★ 7 cited
Neyman-Pearson classification: parametrics and sample size requirement
Xin Tong, Lucy Xia, Jiacheng Wang +1
The Neyman-Pearson (NP) paradigm in binary classification seeks classifiers that achieve a minimal type II error while enforcing the prioritized type I error controlled under some…