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Michael Kuchnik
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2020 – today
- 2024
- [c5]Mubashara Akhtar
, Omar Benjelloun
Croissant: A Metadata Format for ML-Ready Datasets. DEEM@SIGMOD 2024: 1-6 - [i7]Mubashara Akhtar, Omar Benjelloun, Costanza Conforti, Joan Giner-Miguelez, Nitisha Jain, Michael Kuchnik, Quentin Lhoest, Pierre Marcenac, Manil Maskey, Peter Mattson, Luis Oala, Pierre Ruyssen, Rajat Shinde, Elena Simperl, Goeffry Thomas, Slava Tykhonov, Joaquin Vanschoren, Steffen Vogler, Carole-Jean Wu:
Croissant: A Metadata Format for ML-Ready Datasets. CoRR abs/2403.19546 (2024) - [i6]Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, Victor Akinwande, Namir Al-Nuaimi, Najla Alfaraj, Elie Alhajjar, Lora Aroyo, Trupti Bavalatti, Borhane Blili-Hamelin, Kurt D. Bollacker, Rishi Bomassani, Marisa Ferrara Boston, Siméon Campos, Kal Chakra, Canyu Chen, Cody Coleman, Zacharie Delpierre Coudert, Leon Derczynski, Debojyoti Dutta, Ian Eisenberg, James Ezick, Heather Frase, Brian Fuller, Ram Gandikota, Agasthya Gangavarapu, Ananya Gangavarapu, James Gealy, Rajat Ghosh, James Goel, Usman Gohar, Subhra S. Goswami, Scott A. Hale, Wiebke Hutiri, Joseph Marvin Imperial, Surgan Jandial, Nick Judd
Introducing v0.5 of the AI Safety Benchmark from MLCommons. CoRR abs/2404.12241 (2024) - [i5]Nitisha Jain, Mubashara Akhtar, Joan Giner-Miguelez, Rajat Shinde, Joaquin Vanschoren, Steffen Vogler, Subhra S. Goswami, Yuhan Rao, Tim Santos, Luis Oala, Michalis Karamousadakis, Manil Maskey, Pierre Marcenac, Costanza Conforti, Michael Kuchnik, Lora Aroyo, Omar Benjelloun, Elena Simperl:
A Standardized Machine-readable Dataset Documentation Format for Responsible AI. CoRR abs/2407.16883 (2024) - 2023
- [c4]Michael Kuchnik, Virginia Smith, George Amvrosiadis:
Validating Large Language Models with ReLM. MLSys 2023 - 2022
- [c3]Michael Kuchnik, Ana Klimovic
Plumber: Diagnosing and Removing Performance Bottlenecks in Machine Learning Data Pipelines. MLSys 2022 - [i4]Michael Kuchnik, Virginia Smith, George Amvrosiadis:
Validating Large Language Models with ReLM. CoRR abs/2211.15458 (2022) - 2021
- [j4]Michael Kuchnik, George Amvrosiadis, Virginia Smith:
Progressive Compressed Records: Taking a Byte out of Deep Learning Data. Proc. VLDB Endow. 14(11): 2627-2641 (2021) - [i3]Michael Kuchnik, Ana Klimovic, Jiri Simsa, George Amvrosiadis, Virginia Smith:
Plumber: Diagnosing and Removing Performance Bottlenecks in Machine Learning Data Pipelines. CoRR abs/2111.04131 (2021) - 2020
- [j3]Abutalib Aghayev, Sage A. Weil, Michael Kuchnik, Mark Nelson, Gregory R. Ganger, George Amvrosiadis:
The Case for Custom Storage Backends in Distributed Storage Systems. ACM Trans. Storage 16(2): 9:1-9:31 (2020) - [j2]Abutalib Aghayev, Sage A. Weil, Michael Kuchnik, Mark Nelson, Greg Ganger, George Amvrosiadis:
File Systems Unfit as Distributed Storage Back Ends: Lessons from 10 Years of Ceph Evolution. login Usenix Mag. 45(1) (2020)
2010 – 2019
- 2019
- [c2]Michael Kuchnik, Virginia Smith:
Efficient Augmentation via Data Subsampling. ICLR (Poster) 2019 - [c1]Abutalib Aghayev, Sage A. Weil, Michael Kuchnik, Mark Nelson, Gregory R. Ganger, George Amvrosiadis:
File systems unfit as distributed storage backends: lessons from 10 years of Ceph evolution. SOSP 2019: 353-369 - [i2]Michael Kuchnik, George Amvrosiadis, Virginia Smith:
Progressive Compressed Records: Taking a Byte out of Deep Learning Data. CoRR abs/1911.00472 (2019) - 2018
- [j1]George Amvrosiadis, Michael Kuchnik, Jun Woo Park, Chuck Cranor, Gregory R. Ganger, Elisabeth Moore, Nathan DeBardeleben:
The Atlas Cluster Trace Repository. login Usenix Mag. 43(4) (2018) - [i1]Michael Kuchnik, Virginia Smith:
Efficient Augmentation via Data Subsampling. CoRR abs/1810.05222 (2018)
Coauthor Index
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last updated on 2024-08-20 22:52 CEST by the dblp team
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