Abhradeep Thakurta

Name: dblp XML data dump
Creator: Schloss Dagstuhl - Leibniz Center for Informatics
Published: 1993
License: https://creativecommons.org/publicdomain/zero/1.0/
Keywords: dblp, XML, computer science, scholarly publications, metadata

◀ ▶ joint publications with Steve Chien

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Publications

2023
[j5]
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  - journals/jair/PonomarevaHKXDMVCT23
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Natalia Ponomareva, Hussein Hazimeh, Alex Kurakin, Zheng Xu, Carson Denison, H. Brendan McMahan, Sergei Vassilvitskii, Steve Chien, Abhradeep Guha Thakurta:
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy. J. Artif. Intell. Res. 77: 1113-1201 (2023)
[i50]
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  - journals/corr/abs-2303-00654
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Natalia Ponomareva, Hussein Hazimeh, Alex Kurakin, Zheng Xu, Carson Denison, H. Brendan McMahan, Sergei Vassilvitskii, Steve Chien, Abhradeep Thakurta:
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy. CoRR abs/2303.00654 (2023)
2022
[i40]
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  - journals/corr/abs-2201-12328
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Alexey Kurakin, Steve Chien, Shuang Song, Roxana Geambasu, Andreas Terzis, Abhradeep Thakurta:
Toward Training at ImageNet Scale with Differential Privacy. CoRR abs/2201.12328 (2022)
2021
[c37]
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  - conf/aaai/PapernotT0CE21
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Nicolas Papernot, Abhradeep Thakurta, Shuang Song, Steve Chien, Úlfar Erlingsson:
Tempered Sigmoid Activations for Deep Learning with Differential Privacy. AAAI 2021: 9312-9321
[c34]
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  - conf/icml/Chien0KR0T021
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Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang:
Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates. ICML 2021: 1877-1887
[i24]
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  - journals/corr/abs-2107-09802
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Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang:
Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates. CoRR abs/2107.09802 (2021)
2020
[i16]
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  - journals/corr/abs-2007-14191
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Nicolas Papernot, Abhradeep Thakurta, Shuang Song, Steve Chien, Úlfar Erlingsson:
Tempered Sigmoid Activations for Deep Learning with Differential Privacy. CoRR abs/2007.14191 (2020)

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