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Deconstructing Data Reconstruction: Multiclass, Weight Decay and General
  Losses

Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses

4 July 2023
G. Buzaglo
Niv Haim
Gilad Yehudai
Gal Vardi
Yakir Oz
Yaniv Nikankin
Michal Irani
ArXivPDFHTML

Papers citing "Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses"

12 / 12 papers shown
Title
On the Reconstruction of Training Data from Group Invariant Networks
On the Reconstruction of Training Data from Group Invariant Networks
Ran Elbaz
Gilad Yehudai
Meirav Galun
Haggai Maron
56
0
0
25 Nov 2024
Slowing Down Forgetting in Continual Learning
Slowing Down Forgetting in Continual Learning
Pascal Janetzky
Tobias Schlagenhauf
Stefan Feuerriegel
CLL
19
0
0
11 Nov 2024
Evaluating of Machine Unlearning: Robustness Verification Without Prior
  Modifications
Evaluating of Machine Unlearning: Robustness Verification Without Prior Modifications
Heng Xu
Tianqing Zhu
Wanlei Zhou
MU
AAML
13
1
0
14 Oct 2024
Risks When Sharing LoRA Fine-Tuned Diffusion Model Weights
Risks When Sharing LoRA Fine-Tuned Diffusion Model Weights
Dixi Yao
15
1
0
13 Sep 2024
Reconstructing Training Data From Real World Models Trained with
  Transfer Learning
Reconstructing Training Data From Real World Models Trained with Transfer Learning
Yakir Oz
Gilad Yehudai
Gal Vardi
Itai Antebi
Michal Irani
Niv Haim
22
2
0
22 Jul 2024
Data Quality in Edge Machine Learning: A State-of-the-Art Survey
Data Quality in Edge Machine Learning: A State-of-the-Art Survey
M. D. Belgoumri
Mohamed Reda Bouadjenek
Sunil Aryal
Hakim Hacid
14
1
0
01 Jun 2024
Towards Adversarially Robust Dataset Distillation by Curvature Regularization
Towards Adversarially Robust Dataset Distillation by Curvature Regularization
Eric Xue
Yijiang Li
Haoyang Liu
Yifan Shen
Haohan Wang
Haohan Wang
DD
59
7
0
15 Mar 2024
Reconciling AI Performance and Data Reconstruction Resilience for
  Medical Imaging
Reconciling AI Performance and Data Reconstruction Resilience for Medical Imaging
Alexander Ziller
Tamara T. Mueller
Simon Stieger
Leonhard F. Feiner
Johannes Brandt
R. Braren
Daniel Rueckert
Georgios Kaissis
46
1
0
05 Dec 2023
Fishing for User Data in Large-Batch Federated Learning via Gradient
  Magnification
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification
Yuxin Wen
Jonas Geiping
Liam H. Fowl
Micah Goldblum
Tom Goldstein
FedML
65
91
0
01 Feb 2022
Plug-In Inversion: Model-Agnostic Inversion for Vision with Data
  Augmentations
Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations
Amin Ghiasi
Hamid Kazemi
Steven Reich
Chen Zhu
Micah Goldblum
Tom Goldstein
29
15
0
31 Jan 2022
Extracting Training Data from Large Language Models
Extracting Training Data from Large Language Models
Nicholas Carlini
Florian Tramèr
Eric Wallace
Matthew Jagielski
Ariel Herbert-Voss
...
Tom B. Brown
D. Song
Ulfar Erlingsson
Alina Oprea
Colin Raffel
MLAU
SILM
264
1,798
0
14 Dec 2020
When is Memorization of Irrelevant Training Data Necessary for
  High-Accuracy Learning?
When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning?
Gavin Brown
Mark Bun
Vitaly Feldman
Adam D. Smith
Kunal Talwar
242
80
0
11 Dec 2020
1