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Privacy-preserving Learning via Deep Net Pruning

Privacy-preserving Learning via Deep Net Pruning

4 March 2020
Yangsibo Huang
Yushan Su
S. S. Ravi
Zhao Song
Sanjeev Arora
Keqin Li
    MLT
ArXiv (abs)PDFHTML

Papers citing "Privacy-preserving Learning via Deep Net Pruning"

10 / 10 papers shown
SoK: Data Minimization in Machine Learning
SoK: Data Minimization in Machine Learning
Robin Staab
Nikola Jovanović
Kimberly Mai
Prakhar Ganesh
Martin Vechev
Ferdinando Fioretto
Matthew Jagielski
176
1
0
14 Aug 2025
Defending Membership Inference Attacks via Privacy-aware Sparsity Tuning
Defending Membership Inference Attacks via Privacy-aware Sparsity Tuning
Qiang Hu
Hengxiang Zhang
Jianguo Huang
394
3
0
09 Oct 2024
FedP3: Federated Personalized and Privacy-friendly Network Pruning under
  Model Heterogeneity
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity
Kai Yi
Nidham Gazagnadou
Peter Richtárik
Lingjuan Lyu
351
17
0
15 Apr 2024
Just One Byte (per gradient): A Note on Low-Bandwidth Decentralized
  Language Model Finetuning Using Shared Randomness
Just One Byte (per gradient): A Note on Low-Bandwidth Decentralized Language Model Finetuning Using Shared Randomness
E. Zelikman
Qian Huang
Abigail Z. Jacobs
Nick Haber
Noah D. Goodman
214
21
0
16 Jun 2023
Sparsity in neural networks can improve their privacy
Antoine Gonon
Léon Zheng
Clément Lalanne
Quoc-Tung Le
Guillaume Lauga
Can Pouliquen
301
2
0
20 Apr 2023
Model Sparsity Can Simplify Machine Unlearning
Model Sparsity Can Simplify Machine UnlearningNeural Information Processing Systems (NeurIPS), 2023
Jinghan Jia
Jiancheng Liu
Parikshit Ram
Yuguang Yao
Gaowen Liu
Yang Liu
Pranay Sharma
Sijia Liu
MU
1.0K
230
0
11 Apr 2023
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Runhua Xu
Nathalie Baracaldo
J. Joshi
237
156
0
10 Aug 2021
CaPC Learning: Confidential and Private Collaborative Learning
CaPC Learning: Confidential and Private Collaborative LearningInternational Conference on Learning Representations (ICLR), 2021
Christopher A. Choquette-Choo
Natalie Dullerud
Adam Dziedzic
Yunxiang Zhang
S. Jha
Nicolas Papernot
Xiao Wang
FedML
276
65
0
09 Feb 2021
Can we Generalize and Distribute Private Representation Learning?
Can we Generalize and Distribute Private Representation Learning?International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Sheikh Shams Azam
Taejin Kim
Seyyedali Hosseinalipour
Carlee Joe-Wong
S. Bagchi
Christopher G. Brinton
388
12
0
05 Oct 2020
Federated Learning for 6G Communications: Challenges, Methods, and
  Future Directions
Federated Learning for 6G Communications: Challenges, Methods, and Future Directions
Yi Liu
Lizhen Qu
Zehui Xiong
Jiawen Kang
Xiaofei Wang
Dusit Niyato
FedMLAI4CE
279
324
0
04 Jun 2020
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