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Faster Privacy Accounting via Evolving Discretization

Faster Privacy Accounting via Evolving Discretization

10 July 2022
Badih Ghazi
Pritish Kamath
Ravi Kumar
Pasin Manurangsi
ArXivPDFHTML

Papers citing "Faster Privacy Accounting via Evolving Discretization"

11 / 11 papers shown
Title
PREAMBLE: Private and Efficient Aggregation of Block Sparse Vectors and Applications
PREAMBLE: Private and Efficient Aggregation of Block Sparse Vectors and Applications
Hilal Asi
Vitaly Feldman
Hannah Keller
G. Rothblum
Kunal Talwar
FedML
59
1
0
14 Mar 2025
Scalable DP-SGD: Shuffling vs. Poisson Subsampling
Scalable DP-SGD: Shuffling vs. Poisson Subsampling
Lynn Chua
Badih Ghazi
Pritish Kamath
Ravi Kumar
Pasin Manurangsi
Amer Sinha
Chiyuan Zhang
36
5
0
06 Nov 2024
How Private are DP-SGD Implementations?
How Private are DP-SGD Implementations?
Lynn Chua
Badih Ghazi
Pritish Kamath
Ravi Kumar
Pasin Manurangsi
Amer Sinha
Chiyuan Zhang
43
12
0
26 Mar 2024
Privacy-Preserving Instructions for Aligning Large Language Models
Privacy-Preserving Instructions for Aligning Large Language Models
Da Yu
Peter Kairouz
Sewoong Oh
Zheng Xu
34
17
0
21 Feb 2024
Sparsity-Preserving Differentially Private Training of Large Embedding
  Models
Sparsity-Preserving Differentially Private Training of Large Embedding Models
Badih Ghazi
Yangsibo Huang
Pritish Kamath
Ravi Kumar
Pasin Manurangsi
Amer Sinha
Chiyuan Zhang
29
2
0
14 Nov 2023
Selective Pre-training for Private Fine-tuning
Selective Pre-training for Private Fine-tuning
Da Yu
Sivakanth Gopi
Janardhan Kulkarni
Zinan Lin
Saurabh Naik
Tomasz Religa
Jian Yin
Huishuai Zhang
38
19
0
23 May 2023
A Randomized Approach for Tight Privacy Accounting
A Randomized Approach for Tight Privacy Accounting
Jiachen T. Wang
Saeed Mahloujifar
Tong Wu
R. Jia
Prateek Mittal
36
9
0
17 Apr 2023
Private Ad Modeling with DP-SGD
Private Ad Modeling with DP-SGD
Carson E. Denison
Badih Ghazi
Pritish Kamath
Ravi Kumar
Pasin Manurangsi
Krishnagiri Narra
Amer Sinha
A. Varadarajan
Chiyuan Zhang
32
14
0
21 Nov 2022
Composition of Differential Privacy & Privacy Amplification by
  Subsampling
Composition of Differential Privacy & Privacy Amplification by Subsampling
Thomas Steinke
64
49
0
02 Oct 2022
Feature-based Learning for Diverse and Privacy-Preserving Counterfactual
  Explanations
Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations
Vy Vo
Trung Le
Van Nguyen
He Zhao
Edwin V. Bonilla
Gholamreza Haffari
Dinh Q. Phung
CML
50
13
0
27 Sep 2022
The Saddle-Point Accountant for Differential Privacy
The Saddle-Point Accountant for Differential Privacy
Wael Alghamdi
S. Asoodeh
Flavio du Pin Calmon
Juan Felipe Gomez
O. Kosut
Lalitha Sankar
Fei Wei
22
7
0
20 Aug 2022
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