most citedOptimal Federated Learning for Nonparametric Regression with Heterogeneous Distributed Differential Privacy Constraints

2 citations · 3 across the 5 of their papers we have counts for

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5 papers

math.ST2024

Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints

Arnab Auddy, T. Tony Cai, Abhinav Chakraborty

This paper considers minimax and adaptive transfer learning for nonparametric classification under the posterior drift model with distributed differential privacy constraints. Our…

math.ST20242 cited

Optimal Federated Learning for Nonparametric Regression with Heterogeneous Distributed Differential Privacy Constraints

T. Tony Cai, Abhinav Chakraborty, Lasse Vuursteen

This paper studies federated learning for nonparametric regression in the context of distributed samples across different servers, each adhering to distinct differential privacy co…

math.ST20241 cited

Federated Nonparametric Hypothesis Testing with Differential Privacy Constraints: Optimal Rates and Adaptive Tests

T. Tony Cai, Abhinav Chakraborty, Lasse Vuursteen

Federated learning has attracted significant recent attention due to its applicability across a wide range of settings where data is collected and analyzed across disparate locatio…

stat.ME2024

PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model

Abhinav Chakraborty, Anirban Chatterjee, Abhinandan Dalal

The Ising model, originally developed as a spin-glass model for ferromagnetic elements, has gained popularity as a network-based model for capturing dependencies in agents' outputs…

cs.DC2023

Parking Problem by Oblivious Mobile Robots in Infinite Grids

Abhinav Chakraborty, Krishnendu Mukhopadhyaya

In this paper, the parking problem of a swarm of mobile robots has been studied. The robots are deployed at the nodes of an infinite grid, which has a subset of prefixed nodes mark…