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2403.03856
Cited By
Public-data Assisted Private Stochastic Optimization: Power and Limitations
6 March 2024
Enayat Ullah
Michael Menart
Raef Bassily
Cristóbal Guzmán
Raman Arora
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Papers citing
"Public-data Assisted Private Stochastic Optimization: Power and Limitations"
28 / 28 papers shown
Title
Private Distribution Learning with Public Data: The View from Sample Compression
Shai Ben-David
Alex Bie
C. Canonne
Gautam Kamath
Vikrant Singhal
60
12
0
11 Aug 2023
PILLAR: How to make semi-private learning more effective
Francesco Pinto
Yaxian Hu
Fanny Yang
Amartya Sanyal
59
11
0
06 Jun 2023
On Size-Independent Sample Complexity of ReLU Networks
Mark Sellke
27
6
0
03 Jun 2023
Why Is Public Pretraining Necessary for Private Model Training?
Arun Ganesh
Mahdi Haghifam
Milad Nasr
Sewoong Oh
Thomas Steinke
Om Thakkar
Abhradeep Thakurta
Lun Wang
39
37
0
19 Feb 2023
Differentially Private Bias-Term Fine-tuning of Foundation Models
Zhiqi Bu
Yu Wang
Sheng Zha
George Karypis
61
47
0
30 Sep 2022
Private Estimation with Public Data
Alex Bie
Gautam Kamath
Vikrant Singhal
44
30
0
16 Aug 2022
Differentially Private Generalized Linear Models Revisited
R. Arora
Raef Bassily
Cristóbal Guzmán
Michael Menart
Enayat Ullah
FedML
43
17
0
06 May 2022
Private Convex Optimization via Exponential Mechanism
Sivakanth Gopi
Y. Lee
Daogao Liu
100
54
0
01 Mar 2022
Public Data-Assisted Mirror Descent for Private Model Training
Ehsan Amid
Arun Ganesh
Rajiv Mathews
Swaroop Indra Ramaswamy
Shuang Song
Thomas Steinke
Vinith Suriyakumar
Om Thakkar
Abhradeep Thakurta
41
50
0
01 Dec 2021
Differentially Private Fine-tuning of Language Models
Da Yu
Saurabh Naik
A. Backurs
Sivakanth Gopi
Huseyin A. Inan
...
Y. Lee
Andre Manoel
Lukas Wutschitz
Sergey Yekhanin
Huishuai Zhang
177
356
0
13 Oct 2021
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings
Raef Bassily
Cristóbal Guzmán
Michael Menart
58
55
0
12 Jul 2021
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning
Da Yu
Huishuai Zhang
Wei Chen
Tie-Yan Liu
FedML
SILM
101
113
0
25 Feb 2021
Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification
Yingxue Zhou
Zhiwei Steven Wu
A. Banerjee
48
108
0
07 Jul 2020
A Primer on Private Statistics
Gautam Kamath
Jonathan R. Ullman
49
48
0
30 Apr 2020
Private Query Release Assisted by Public Data
Raef Bassily
Albert Cheu
Shay Moran
Aleksandar Nikolov
Jonathan R. Ullman
Zhiwei Steven Wu
104
48
0
23 Apr 2020
Limits of Private Learning with Access to Public Data
N. Alon
Raef Bassily
Shay Moran
21
48
0
25 Oct 2019
FedMD: Heterogenous Federated Learning via Model Distillation
Daliang Li
Junpu Wang
FedML
75
845
0
08 Oct 2019
Private Stochastic Convex Optimization with Optimal Rates
Raef Bassily
Vitaly Feldman
Kunal Talwar
Abhradeep Thakurta
48
240
0
27 Aug 2019
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy
T. Tony Cai
Yichen Wang
Linjun Zhang
51
165
0
12 Feb 2019
Scalable Private Learning with PATE
Nicolas Papernot
Shuang Song
Ilya Mironov
A. Raghunathan
Kunal Talwar
Ulfar Erlingsson
83
608
0
24 Feb 2018
Size-Independent Sample Complexity of Neural Networks
Noah Golowich
Alexander Rakhlin
Ohad Shamir
86
547
0
18 Dec 2017
Spectrally-normalized margin bounds for neural networks
Peter L. Bartlett
Dylan J. Foster
Matus Telgarsky
ODL
130
1,208
0
26 Jun 2017
Generalization for Adaptively-chosen Estimators via Stable Median
Vitaly Feldman
Thomas Steinke
109
42
0
15 Jun 2017
Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Nicolas Papernot
Martín Abadi
Ulfar Erlingsson
Ian Goodfellow
Kunal Talwar
52
1,012
0
18 Oct 2016
Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization
Vitaly Feldman
Cristóbal Guzmán
Santosh Vempala
61
89
0
30 Dec 2015
Between Pure and Approximate Differential Privacy
Thomas Steinke
Jonathan R. Ullman
FedML
52
159
0
24 Jan 2015
Private Learning and Sanitization: Pure vs. Approximate Differential Privacy
A. Beimel
Kobbi Nissim
Uri Stemmer
57
194
0
10 Jul 2014
Fingerprinting Codes and the Price of Approximate Differential Privacy
Mark Bun
Jonathan R. Ullman
Salil P. Vadhan
FedML
45
211
0
13 Nov 2013
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