Publications (Google Scholar)

Thesis

Book Chapter

  • A.K. Sahu and S. Kar, Distributed recursive testing of composite hypothesis in multi-agent networks, in Data Fusion in Wireless Sensor Networks: A Statistical Signal Processing Perspective, Domenico Ciuonzo and Pierluigi Salvo Rossi, Eds., Institution of Engineering & Technology, 2019

Patents

Preprints

  • A. S. Bedi, C. Fan, A. K. Sahu, A. Koppel, F. Huang, B. Saddler and D. Manocha, FedBC: Calibrating Global and Local Models via Federated Learning Beyond Consensus, May 2022

Journal Papers

Conference Papers

  • Z. Jiang, J. Francis, A.K. Sahu, S. Munir, C. Shelton, A. Rowe and M. Berges, Data-driven Thermal Model Inference with ARMAX, in Smart Environments, based on Normalized Mutual Information, In Proceedings of American Control Conference, ACC 2018

Invited Talks

  • “Distributed Inference in Large-scale Stochastic Systems: Imperfect Communication” Department of Electronics and Electrical Communications Engineering, IIT Kharagpur, August 2016

  • “Distributed Weighted Non-linear least Squares and Recursive Composite Hypothesis Testing: A consensus+innovations approach”, Mcgill University, July 2017

  • “Distributed Recursive Composite Hypothesis Testing: A consensus+innovations approach”, IFORS 2017, July 2017

  • “Online Learning in Large Scale Stochastic Systems”, IBM India Research Lab, August 2017