Conformal Distributed Remote Inference in Sensor Networks Under Reliability and Communication Constraints

Autor:	Zhu, Meiyi, Zecchin, Matteo, Park, Sangwoo, Guo, Caili, Feng, Chunyan, Popovski, Petar, Simeone, Osvaldo
Rok vydání:	2024
Předmět:	Electrical Engineering and Systems Science - Signal Processing Computer Science - Information Theory Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	This paper presents communication-constrained distributed conformal risk control (CD-CRC) framework, a novel decision-making framework for sensor networks under communication constraints. Targeting multi-label classification problems, such as segmentation, CD-CRC dynamically adjusts local and global thresholds used to identify significant labels with the goal of ensuring a target false negative rate (FNR), while adhering to communication capacity limits. CD-CRC builds on online exponentiated gradient descent to estimate the relative quality of the observations of different sensors, and on online conformal risk control (CRC) as a mechanism to control local and global thresholds. CD-CRC is proved to offer deterministic worst-case performance guarantees in terms of FNR and communication overhead, while the regret performance in terms of false positive rate (FPR) is characterized as a function of the key hyperparameters. Simulation results highlight the effectiveness of CD-CRC, particularly in communication resource-constrained environments, making it a valuable tool for enhancing the performance and reliability of distributed sensor networks. Comment: 14 pages, 15 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2409.07902 Zobrazit plný text záznamu View this record from Arxiv