NeSSA: Near-Storage Data Selection for Accelerated Machine Learning Training-Reference-Cited by-同舟云学术

NeSSA: Near-Storage Data Selection for Accelerated Machine Learning Training

Published:2023-07-09 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 15th ACM Workshop on Hot Topics in Storage and File Systems
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Author:

Prakriya Neha¹^ORCID,Yang Yu²^ORCID,Mirzasoleiman Baharan²^ORCID,Hsieh Cho-Jui²^ORCID,Cong Jason¹^ORCID

Affiliation:

1. UCLA, Los Angeles, United States of America

2. UCLA, Los Angeles, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3599691.3603404

Reference46 articles.

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2. Ben Sorscher , Robert Geirhos , Shashank Shekhar , Surya Ganguli , and Ari S. Morcos . Beyond Neural Scaling Laws: Beating Power Law Scaling Via Data Pruning . In Alice H. Oh , Alekh Agarwal, Danielle Belgrave, and Kyunghyun Cho, editors, Advances in Neural Information Processing Systems, 2022 . URL https://openreview.net/forum?id=UmvSlP-PyV. Ben Sorscher, Robert Geirhos, Shashank Shekhar, Surya Ganguli, and Ari S. Morcos. Beyond Neural Scaling Laws: Beating Power Law Scaling Via Data Pruning. In Alice H. Oh, Alekh Agarwal, Danielle Belgrave, and Kyunghyun Cho, editors, Advances in Neural Information Processing Systems, 2022. URL https://openreview.net/forum?id=UmvSlP-PyV.

3. ImageNet: A large-scale hierarchical image database

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5. The importance of better models in stochastic optimization

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