activity
20172022
most citedA Mean Field Theory of Batch Normalization

54 citations · 161 across the 5 of their papers we have counts for

collaborators
Showing 2019Show all

8 papers · 1 filter

math.AC2019

Free resolutions of function classes via order complexes

Justin Chen, Christopher Eur, Greg Yang +1

Function classes are collections of Boolean functions on a finite set, which are fundamental objects of study in theoretical computer science. We study algebraic properties of idea…

cs.LG2019

A Fine-Grained Spectral Perspective on Neural Networks

Greg Yang, Hadi Salman

Are neural networks biased toward simple functions? Does depth always help learn more complex features? Is training the last layer of a network as good as training all layers? How…

cs.LG2019

Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers

Hadi Salman, Greg Yang, Jerry Li +4

Recent works have shown the effectiveness of randomized smoothing as a scalable technique for building neural network-based classifiers that are provably robust to -norm ad…

cs.NE201954 cited

A Mean Field Theory of Batch Normalization

Greg Yang, Jeffrey Pennington, Vinay Rao +2

We develop a mean field theory for batch normalization in fully-connected feedforward neural networks. In so doing, we provide a precise characterization of signal propagation and…

cs.AI201929 cited

NAIL: A General Interactive Fiction Agent

Matthew Hausknecht, Ricky Loynd, Greg Yang +2

Interactive Fiction (IF) games are complex textual decision making problems. This paper introduces NAIL, an autonomous agent for general parser-based IF games. NAIL won the 2018 Te…

cs.LG2019

A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks

Hadi Salman, Greg Yang, Huan Zhang +2

Verification of neural networks enables us to gauge their robustness against adversarial attacks. Verification algorithms fall into two categories: exact verifiers that run in expo…