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1606.03572
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Differentially Private Random Decision Forests using Smooth Sensitivity
11 June 2016
Sam Fletcher
M. Islam
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Papers citing
"Differentially Private Random Decision Forests using Smooth Sensitivity"
21 / 21 papers shown
Differentially Private Selection using Smooth Sensitivity
IEEE Symposium on Security and Privacy (S&P), 2025
Iago C. Chaves
V. A. E. Farias
Amanda Perez
Diego Parente
Javam C. Machado
183
0
0
10 Apr 2025
Training Set Reconstruction from Differentially Private Forests: How Effective is DP?
Alice Gorgé
Julien Ferry
Sébastien Gambs
Thibaut Vidal
401
1
0
07 Feb 2025
Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
International Conference on Learning Representations (ICLR), 2024
Fengyu Gao
Ruida Zhou
T. Wang
Cong Shen
Jing Yang
377
8
0
15 Oct 2024
Smooth Sensitivity for Learning Differentially-Private yet Accurate Rule Lists
Timothée Ly
Julien Ferry
Marie-José Huguet
Sébastien Gambs
Ulrich Aïvodji
232
0
0
18 Mar 2024
Classification with Partially Private Features
Zeyu Shen
A. Krishnaswamy
Janardhan Kulkarni
Kamesh Munagala
357
4
0
11 Dec 2023
Privacy-Preserving Federated Learning over Vertically and Horizontally Partitioned Data for Financial Anomaly Detection
S. Kadhe
Heiko Ludwig
Nathalie Baracaldo
Alan King
Yi Zhou
...
Ryo Kawahara
Nir Drucker
Hayim Shaul
Eyal Kushnir
Omri Soceanu
FedML
235
5
0
30 Oct 2023
Differentially-Private Decision Trees and Provable Robustness to Data Poisoning
D. Vos
Jelle Vos
Tianyu Li
Z. Erkin
S. Verwer
FedML
310
4
0
24 May 2023
Private Multi-Winner Voting for Machine Learning
Proceedings on Privacy Enhancing Technologies (PoPETs), 2022
Adam Dziedzic
Christopher A. Choquette-Choo
Natalie Dullerud
Vinith Suriyakumar
Ali Shahin Shamsabadi
Muhammad Ahmad Kaleem
S. Jha
Nicolas Papernot
Xiao Wang
280
1
0
23 Nov 2022
A General Framework for Auditing Differentially Private Machine Learning
Neural Information Processing Systems (NeurIPS), 2022
Fred Lu
Joseph Munoz
Maya Fuchs
Tyler LeBlond
Elliott Zaresky-Williams
Edward Raff
Francis Ferraro
Brian Testa
FedML
320
51
0
16 Oct 2022
Federated Boosted Decision Trees with Differential Privacy
Conference on Computer and Communications Security (CCS), 2022
Samuel Maddock
Graham Cormode
Tianhao Wang
Carsten Maple
S. Jha
FedML
256
47
0
06 Oct 2022
How unfair is private learning ?
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
Amartya Sanyal
Yaxian Hu
Fanny Yang
FaML
FedML
456
27
0
08 Jun 2022
Oblique and rotation double random forest
Neural Networks (NN), 2021
M. A. Ganaie
M. Tanveer
Ponnuthurai Nagaratnam Suganthan
V. Snás̃el
246
73
0
03 Nov 2021
Data Security and Privacy in Cloud Computing: Concepts and Emerging Trends
Rishabh Gupta
D. Saxena
Ashutosh Kumar Singh
134
0
0
21 Aug 2021
SoK: Privacy-Preserving Collaborative Tree-based Model Learning
Proceedings on Privacy Enhancing Technologies (PoPETs), 2021
Sylvain Chatel
Apostolos Pyrgelis
J. Troncoso-Pastoriza
Jean-Pierre Hubaux
352
18
0
16 Mar 2021
Machine Unlearning for Random Forests
International Conference on Machine Learning (ICML), 2020
Jonathan Brophy
Daniel Lowd
MU
436
221
0
11 Sep 2020
Not one but many Tradeoffs: Privacy Vs. Utility in Differentially Private Machine Learning
Benjamin Zi Hao Zhao
M. Kâafar
N. Kourtellis
216
37
0
20 Aug 2020
Anonymizing Machine Learning Models
Abigail Goldsteen
Gilad Ezov
Ron Shmelkin
Micha Moffie
Ariel Farkash
MIACV
259
9
0
26 Jul 2020
Boosted and Differentially Private Ensembles of Decision Trees
Richard Nock
Wilko Henecka
262
2
0
26 Jan 2020
Differentially Private Regression and Classification with Sparse Gaussian Processes
Journal of machine learning research (JMLR), 2019
M. Smith
Mauricio A. Alvarez
Neil D. Lawrence
151
6
0
19 Sep 2019
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation
Neural Information Processing Systems (NeurIPS), 2019
Mark Bun
Thomas Steinke
314
86
0
06 Jun 2019
PUTWorkbench: Analysing Privacy in AI-intensive Systems
S. Srivastava
Vinay P. Namboodiri
T. Prabhakar
113
1
0
05 Feb 2019
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