316 citations · 496 across the 17 of their papers we have counts for
3 papers · 1 filter
On Accelerating Distributed Convex Optimizations
Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
This paper studies a distributed multi-agent convex optimization problem. The system comprises multiple agents in this problem, each with a set of local data points and an associat…
Generalized AdaGrad (G-AdaGrad) and Adam: A State-Space Perspective
Kushal Chakrabarti, Nikhil Chopra
Accelerated gradient-based methods are being extensively used for solving non-convex machine learning problems, especially when the data points are abundant or the available data i…
Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem
Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
This paper considers the problem of multi-agent distributed linear regression in the presence of system noises. In this problem, the system comprises multiple agents wherein each a…