2 citations · 4 across the 10 of their papers we have counts for
12 papers
Network Intervention by Polling Strategic Agents
Chenyu Zhang, Rohit Parasnis, Saurabh Amin
A planner in a network of strategic agents faces three entangled challenges: the optimum depends on agents' private information, queried agents may misreport to steer the outcome,…
Adversarial Node Placement in Decentralized Federated Learning: Maximum Spanning-Centrality Strategy and Performance Analysis
Adam Piaseczny, Eric Ruzomberka, Rohit Parasnis +1
As Federated Learning (FL) becomes more widespread, there is growing interest in its decentralized variants. Decentralized FL leverages the benefits of fast and energy-efficient de…
Optimal Interventions in Coupled-Activity Network Games: Application to Sustainable Forestry
Rohit Parasnis, Saurabh Amin
We address the challenge of promoting sustainable practices in production forests managed by strategic entities (agents) that harvest agricultural commodities under concession agre…
Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees
Shahryar Zehtabi, Dong-Jun Han, Rohit Parasnis +2
Decentralized federated learning (DFL) captures FL settings where both (i) model updates and (ii) model aggregations are exclusively carried out by the clients without a central se…
The Impact of Adversarial Node Placement in Decentralized Federated Learning Networks
Adam Piaseczny, Eric Ruzomberka, Rohit Parasnis +1
As Federated Learning (FL) grows in popularity, new decentralized frameworks are becoming widespread. These frameworks leverage the benefits of decentralized environments to enable…
Distributed Linear Solvers and Data Heterogeneity
Boris Velasevic, Rohit Parasnis, Christopher G. Brinton +1
We consider the problem of solving a large-scale system of linear equations in a distributed/federated setting. The taskmaster solves the system with the help of a set of machines,…
Connectivity-Aware Semi-Decentralized Federated Learning over Time-Varying D2D Networks
Rohit Parasnis, Seyyedali Hosseinalipour, Yun-Wei Chu +2
Semi-decentralized federated learning blends the conventional device to-server (D2S) interaction structure of federated model training with localized device-to-device (D2D) communi…
A Random Adaptation Perspective on Distributed Averaging
Rohit Parasnis, Ashwin Verma, Massimo Franceschetti +1
We propose a random adaptation variant of time-varying distributed averaging dynamics in discrete time. We show that this leads to novel interpretations of fundamental concepts in…
A Perron-Frobenius Theorem for Strongly Aperiodic Stochastic Chains
Rohit Parasnis, Massimo Franceschetti, Behrouz Touri
We derive a generalization of the Perron-Frobenius theorem to time-varying row-stochastic matrices as follows: using Kolmogorov's concept of absolute probability sequences, which a…
Usefulness of the Age-Structured SIR Dynamics in Modelling COVID-19
Rohit Parasnis, Ryosuke Kato, Amol Sakhale +2
We examine the age-structured SIR model, a variant of the classical Susceptible-Infected-Recovered (SIR) model of epidemic propagation, in the context of COVID-19. In doing so, we…
Non-Bayesian Social Learning on Random Digraphs with Aperiodically Varying Network Connectivity
Rohit Parasnis, Massimo Franceschetti, Behrouz Touri
We study non-Bayesian social learning on random directed graphs and show that under mild connectivity assumptions, all the agents almost surely learn the true state of the world as…
On the Convergence Properties of Social Hegselmann-Krause Dynamics
Rohit Parasnis, Massimo Franceschetti, Behrouz Touri
We study the convergence properties of Social Hegselmann-Krause dynamics, a {variant} of the Hegselmann-Krause (HK) model of opinion dynamics where a physical connectivity graph th…