42 citations · 111 across the 18 of their papers we have counts for
5 papers · 1 filter
Fundamental limits of over-the-air optimization: Are analog schemes optimal?
Shubham K Jha, Prathamesh Mayekar, Himanshu Tyagi
We consider over-the-air convex optimization on a dimensional space where coded gradients are sent over an additive Gaussian noise channel with variance . The codewords sa…
Optimal Rates for Nonparametric Density Estimation under Communication Constraints
Jayadev Acharya, Clément L. Canonne, Aditya Vikram Singh +1
We consider density estimation for Besov spaces when each sample is quantized to only a limited number of bits. We provide a noninteractive adaptive estimator that exploits the spa…
Information-constrained optimization: can adaptive processing of gradients help?
Jayadev Acharya, Clément L. Canonne, Prathamesh Mayekar +1
We revisit first-order optimization under local information constraints such as local privacy, gradient quantization, and computational constraints limiting access to a few coordin…
Phase Transitions for Support Recovery from Gaussian Linear Measurements
Lekshmi Ramesh, Chandra R. Murthy, Himanshu Tyagi
We study the problem of recovering the common -sized support of a set of samples of dimension , using noisy linear measurements per sample. Most prior work has focuse…
Inference under Information Constraints III: Local Privacy Constraints
Jayadev Acharya, Clément L. Canonne, Cody Freitag +2
We study goodness-of-fit and independence testing of discrete distributions in a setting where samples are distributed across multiple users. The users wish to preserve the privacy…