Approximating Memorization Using Loss Surface Geometry for Dataset Pruning and Summarization
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acm = {3671985},
author = {Agiollo, Andrea and Young In Kim and Khanna, Rajiv},
dblp = {conf/kdd/AgiolloKK24},
doi = {10.1145/3637528.3671985},
journal = {Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '24), August 25–29, 2024, Barcelona, Spain},
keywords = {Neural Networks, Data-efficient Learning, Memorization, Flatness},
month = aug,
numpages = 12,
pages = {17--28},
publisher = {ACM},
scholar = {8151925308990231563},
title = {Approximating Memorization Using Loss Surface Geometry for Dataset Pruning and Summarization},
url = {https://dl.acm.org/doi/10.1145/3637528.3671985},
urlopenaccess = {https://dl.acm.org/doi/pdf/10.1145/3637528.3671985},
urlpdf = {https://dl.acm.org/doi/pdf/10.1145/3637528.3671985},
year = 2024
}