Communication-efficient Conformal Prediction for Distributed Datasets

Nery Riquelme-Granada; Zhiyuan Luo; Khuong An Nguyen

Communication-efficient Conformal Prediction for Distributed Datasets

Nery Riquelme-Granada, Zhiyuan Luo, Khuong An Nguyen

School of Arch, Tech and Eng

Research output: Contribution to conference › Abstract › peer-review

Abstract

Coresets have been proven useful in accelerating the computation of inductive conformal predictors (ICP) when the training data becomes large in size.

This work shows that coreset-based conformal predictors are not only computationally efficient in the centralised setting, but may also naturally be used in scenarios where the dataset of interested in inherently distributed.

Original language	English
Number of pages	3
Publication status	Published - 26 Aug 2022
Event	11th Symposium on Conformal and Probabilistic Prediction with Applications - University of Brighton, Brighton, United Kingdom Duration: 24 Aug 2022 → 26 Aug 2022 https://copa-conference.com/

Conference

Conference	11th Symposium on Conformal and Probabilistic Prediction with Applications
Abbreviated title	COPA 2022
Country/Territory	United Kingdom
City	Brighton
Period	24/08/22 → 26/08/22
Internet address	https://copa-conference.com/

Access to Document

http://proceedings.mlr.press/v179/

Cite this

@conference{ae6443b9966c4884ae86c8794de354ba,

title = "Communication-efficient Conformal Prediction for Distributed Datasets",

abstract = "Coresets have been proven useful in accelerating the computation of inductive conformal predictors (ICP) when the training data becomes large in size.This work shows that coreset-based conformal predictors are not only computationally efficient in the centralised setting, but may also naturally be used in scenarios where the dataset of interested in inherently distributed.",

author = "Nery Riquelme-Granada and Zhiyuan Luo and Nguyen, {Khuong An}",

year = "2022",

month = aug,

day = "26",

language = "English",

note = "11th Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2022 ; Conference date: 24-08-2022 Through 26-08-2022",

url = "https://copa-conference.com/",

}

TY - CONF

T1 - Communication-efficient Conformal Prediction for Distributed Datasets

AU - Riquelme-Granada, Nery

AU - Luo, Zhiyuan

AU - Nguyen, Khuong An

PY - 2022/8/26

Y1 - 2022/8/26

N2 - Coresets have been proven useful in accelerating the computation of inductive conformal predictors (ICP) when the training data becomes large in size.This work shows that coreset-based conformal predictors are not only computationally efficient in the centralised setting, but may also naturally be used in scenarios where the dataset of interested in inherently distributed.

AB - Coresets have been proven useful in accelerating the computation of inductive conformal predictors (ICP) when the training data becomes large in size.This work shows that coreset-based conformal predictors are not only computationally efficient in the centralised setting, but may also naturally be used in scenarios where the dataset of interested in inherently distributed.

UR - https://proceedings.mlr.press/v179/riquelme-granada22a/riquelme-granada22a.pdf

M3 - Abstract

T2 - 11th Symposium on Conformal and Probabilistic Prediction with Applications

Y2 - 24 August 2022 through 26 August 2022

ER -

Communication-efficient Conformal Prediction for Distributed Datasets

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Cite this