Towards Reliable Rare Category Analysis on Graphs via Individual Calibration-Reference-Cited by-同舟云学术

Towards Reliable Rare Category Analysis on Graphs via Individual Calibration

Published:2023-08-04 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Wu Longfeng¹^ORCID,Lei Bowen²^ORCID,Xu Dongkuan³^ORCID,Zhou Dawei¹^ORCID

Affiliation:

1. Virginia Tech, Blacksburg, VA, USA

2. Texas A&M University, College Station, TX, USA

3. North Carolina State University, Raleigh, NC, USA

Funder

CCI

Deloitte

Cisco

4-VA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3580305.3599525

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2. Arsenii Ashukha , Alexander Lyzhov , Dmitry Molchanov , and Dmitry Vetrov . 2020. Pitfalls of in-domain uncertainty estimation and ensembling in deep learning. arXiv preprint arXiv:2002.06470 ( 2020 ). Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov, and Dmitry Vetrov. 2020. Pitfalls of in-domain uncertainty estimation and ensembling in deep learning. arXiv preprint arXiv:2002.06470 (2020).

3. Generating synthetic data in finance

4. Rina Foygel Barber Emmanuel J Candes Aaditya Ramdas and Ryan J Tibshirani. 2021. Predictive inference with the jackknife. (2021). Rina Foygel Barber Emmanuel J Candes Aaditya Ramdas and Ryan J Tibshirani. 2021. Predictive inference with the jackknife. (2021).

5. Large Scale Detection of Irregularities in Accounting Data

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