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From the 1 of 13 linked papers with an AI index.

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13 papers

cs.LG2026

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…

cs.DC2026

Decentralized Operations of Decarbonized Chemical Plants with Renewable-driven Transmission Systems

Richard Reed, Kazi Arman Ahmed, Saba Ghasemi +2

Electrification of ethane cracking offers a promising pathway to industrial decarbonization, provided that the electricity is sourced from renewable energy. However, integrating el…

cs.CR2026

CoSMeTIC: Zero-Knowledge Computational Sparse Merkle Trees with Inclusion-Exclusion Proofs for Clinical Research

Mohammad Shahid, Paritosh Ramanan, Mohammad Fili +2

Analysis of clinical data is a cornerstone of biomedical research with applications in areas such as genomic testing and response characterization of therapeutic drugs. Maintaining…

cs.CR2026

PRECISE: Private Regulatory Compliance for Cyberattack Detection on Critical Infrastructure Systems

Sathwik Yamana, Paritosh Ramanan, H. M. Mohaimanul Islam +1

Industrial control systems are a fundamental component of critical infrastructure networks (CIN) such as gas, water, and power. With the growing risk of cyberattacks, regulatory co…

math.OC2026

Toward Decarbonization of Chemical Manufacturing: Joint Optimization of Unit Commitment and Microgrid Operations

Saba Ghasemi Naraghi, Richard Reed, Tylee Kareck +2

The electrification of chemical process heating is essential to industrial decarbonization and sustainable manufacturing of chemical products. Joint optimization of electrified che…

cs.LG2026

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…