From the 1 of 14 linked papers with an AI index.
5 papers · 1 filter
Privacy-Aware Collaborative and Distributed Bayesian Optimization
Aditya Rane, Sathwik Yamana, Paritosh Ramanan +2
The paper introduces a collaborative meta‑learning framework for distributed Bayesian optimization that avoids sharing raw data, examines privacy leaks from gradient sharing, and e…
Learning Unknown Interdependencies for Decentralized Root Cause Analysis in Nonlinear Dynamical Systems
Ayush Mohanty, Paritosh Ramanan, Nagi Gebraeel
Root cause analysis (RCA) in networked industrial systems, such as supply chains and power networks, is notoriously difficult due to unknown and dynamically evolving interdependenc…
Federated Granger Causality Learning for Interdependent Clients with State Space Representation
Ayush Mohanty, Nazal Mohamed, Paritosh Ramanan +1
Advanced sensors and IoT devices have improved the monitoring and control of complex industrial enterprises. They have also created an interdependent fabric of geographically distr…
Text embedding models can be great data engineers
Iman Kazemian, Paritosh Ramanan, Murat Yildirim
Data engineering pipelines are essential - albeit costly - components of predictive analytics frameworks requiring significant engineering time and domain expertise for carrying ou…
SplitVAEs: Decentralized scenario generation from siloed data for stochastic optimization problems
H M Mohaimanul Islam, Huynh Q. N. Vo, Paritosh Ramanan
Stochastic optimization problems in large-scale multi-stakeholder networked systems (e.g., power grids and supply chains) rely on data-driven scenarios to encapsulate complex spati…