Co-occurring keywords · papers mentioning both
Papers
A Depth Hierarchy for Computing the Maximum in ReLU Networks via Extremal Graph Theory
COLT 2026
Blessing of Depth in Linear Regression: Deeper Models Have Flatter Landscape Around the True Solution
NeurIPS 2022
Deep Limits and a Cut-Off Phenomenon for Neural Networks
JMLR 2022
Depth and Feature Learning are Provably Beneficial for Neural Network Discriminators
COLT 2022
Joint Inference for Neural Network Depth and Dropout Regularization
NeurIPS 2021
Depth Uncertainty in Neural Networks
NeurIPS 2020
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth
NeurIPS 2020
How Neural Network Depth Compensates for HMM Conditional Independence Assumptions in DNN-HMM Acoustic Models
Interspeech 2016