20 citations · 68 across the 9 of their papers we have counts for
9 papers
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning
Prashant Khanduri, Pranay Sharma, Haibo Yang +4
Federated Learning (FL) refers to the paradigm where multiple worker nodes (WNs) build a joint model by using local data. Despite extensive research, for a generic non-convex FL pr…
Joint Collaboration and Compression Design for Distributed Sequential Estimation in a Wireless Sensor Network
Xiancheng Cheng, Prashant Khanduri, Boxiao Chen +1
In this work, we propose a joint collaboration-compression framework for sequential estimation of a random vector parameter in a resource constrained wireless sensor network (WSN).…
Distributed Stochastic Non-Convex Optimization: Momentum-Based Variance Reduction
Prashant Khanduri, Pranay Sharma, Swatantra Kafle +3
In this work, we propose a distributed algorithm for stochastic non-convex optimization. We consider a worker-server architecture where a set of worker nodes (WNs) in collabora…
On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit
Pranay Sharma, Prashant Khanduri, Lixin Shen +2
In this work, we consider a distributed online convex optimization problem, with time-varying (potentially adversarial) constraints. A set of nodes, jointly aim to minimize a globa…
Byzantine Resilient Non-Convex SVRG with Distributed Batch Gradient Computations
Prashant Khanduri, Saikiran Bulusu, Pranay Sharma +1
In this work, we consider the distributed stochastic optimization problem of minimizing a non-convex function in an adversarial sett…
Parallel Restarted SPIDER -- Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity
Pranay Sharma, Swatantra Kafle, Prashant Khanduri +3
In this paper, we propose a distributed algorithm for stochastic smooth, non-convex optimization. We assume a worker-server architecture where nodes, each having (potential…