activity
20182021
most citedLower Bounds for Learning Distributions under Communication Constraints via Fisher Information

13 citations · 15 across the 3 of their papers we have counts for

collaborators

8 papers

cs.IT2021

Over-the-Air Statistical Estimation

Chuan-Zheng Lee, Leighton Pate Barnes, Ayfer Ozgur

We study schemes and lower bounds for distributed minimax statistical estimation over a Gaussian multiple-access channel (MAC) under squared error loss, in a framework combining st…

cs.IT2020

Strong Privacy and Utility Guarantee: Over-the-Air Statistical Estimation

Wenhao Zhan

We consider the privacy problem of statistical estimation from distributed data, where users communicate to a central processor over a Gaussian multiple-access channel(MAC). To avo…

cs.IT2020

Fisher information under local differential privacy

Leighton Pate Barnes, Wei-Ning Chen, Ayfer Ozgur

We develop data processing inequalities that describe how Fisher information from statistical samples can scale with the privacy parameter under local differential pr…

cs.LG2020

rTop-k: A Statistical Estimation Approach to Distributed SGD

Leighton Pate Barnes, Huseyin A. Inan, Berivan Isik +1

The large communication cost for exchanging gradients between different nodes significantly limits the scalability of distributed training for large-scale learning models. Motivate…

cs.IT2020

The Courtade-Kumar Most Informative Boolean Function Conjecture and a Symmetrized Li-Médard Conjecture are Equivalent

Leighton Pate Barnes, Ayfer Özgür

We consider the Courtade-Kumar most informative Boolean function conjecture for balanced functions, as well as a conjecture by Li and Médard that dictatorship functions also maximi…

cs.IT20192 cited

Minimax Bounds for Distributed Logistic Regression

Leighton Pate Barnes, Ayfer Ozgur

We consider a distributed logistic regression problem where labeled data pairs for are distributed across multiple machines…