Federated Inference with Reliable Uncertainty Quantification over
Wireless Channels via Conformal Prediction
- URL: http://arxiv.org/abs/2308.04237v2
- Date: Fri, 15 Dec 2023 17:30:52 GMT
- Title: Federated Inference with Reliable Uncertainty Quantification over
Wireless Channels via Conformal Prediction
- Authors: Meiyi Zhu, Matteo Zecchin, Sangwoo Park, Caili Guo, Chunyan Feng,
Osvaldo Simeone
- Abstract summary: We study a wireless federated inference scenario in which devices and a server share a pre-trained machine learning model.
We introduce a novel protocol, termed wireless federated conformal prediction (WFCP)
WFCP is proved to provide formal reliability guarantees in terms of coverage of the predicted set produced by the server.
- Score: 43.36472219160387
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In this paper, we consider a wireless federated inference scenario in which
devices and a server share a pre-trained machine learning model. The devices
communicate statistical information about their local data to the server over a
common wireless channel, aiming to enhance the quality of the inference
decision at the server. Recent work has introduced federated conformal
prediction (CP), which leverages devices-to-server communication to improve the
reliability of the server's decision. With federated CP, devices communicate to
the server information about the loss accrued by the shared pre-trained model
on the local data, and the server leverages this information to calibrate a
decision interval, or set, so that it is guaranteed to contain the correct
answer with a pre-defined target reliability level. Previous work assumed
noise-free communication, whereby devices can communicate a single real number
to the server. In this paper, we study for the first time federated CP in a
wireless setting. We introduce a novel protocol, termed wireless federated
conformal prediction (WFCP), which builds on type-based multiple access (TBMA)
and on a novel quantile correction strategy. WFCP is proved to provide formal
reliability guarantees in terms of coverage of the predicted set produced by
the server. Using numerical results, we demonstrate the significant advantages
of WFCP against digital implementations of existing federated CP schemes,
especially in regimes with limited communication resources and/or large number
of devices.
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