3 citations · 3 across the 4 of their papers we have counts for
4 papers
Fundamental Limits of Distributed Optimization over Multiple Access Channel
Shubham Jha
We consider distributed optimization over a -dimensional space, where remote clients send coded gradient estimates over an {\em additive Gaussian Multiple Access Channel (MA…
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…
Universal Gaussian Quantization with Side Information using Polar Lattices
Shubham Jha
We consider universal quantization with side information for Gaussian observations, where the side information is a noisy version of the sender's observation with noise variance un…
Wyner-Ziv Estimators for Distributed Mean Estimation with Side Information and Optimization
Prathamesh Mayekar, Shubham Jha, Ananda Theertha Suresh +1
Communication efficient distributed mean estimation is an important primitive that arises in many distributed learning and optimization scenarios such as federated learning. Withou…