Reconstructing Training Data from Trained Neural Networks

15 June 2022

Gal Vardi

Papers citing "Reconstructing Training Data from Trained Neural Networks"

45 / 95 papers shown

Title
On original and latent space connectivity in deep neural networks Boyang Gu Anastasia Borovykh GNN 3DPC 17 1 0 12 Nov 2023
Learning Human Action Recognition Representations Without Real Humans Howard Zhong Samarth Mishra Donghyun Kim SouYoung Jin Rameswar Panda Hildegard Kuehne Leonid Karlinsky Venkatesh Saligrama Aude Oliva Rogerio Feris 24 3 0 10 Nov 2023
Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks Jiayuan Ye Zhenyu Zhu Fanghui Liu Reza Shokri V. Cevher 22 12 0 31 Oct 2023
One or Two Things We know about Concept Drift -- A Survey on Monitoring Evolving Environments Fabian Hinder Valerie Vaquet Barbara Hammer 14 7 0 24 Oct 2023
User Inference Attacks on Large Language Models Nikhil Kandpal Krishna Pillutla Alina Oprea Peter Kairouz Christopher A. Choquette-Choo Zheng Xu SILM AAML 19 15 0 13 Oct 2023
A Survey of Data Security: Practices from Cybersecurity and Challenges of Machine Learning Padmaksha Roy Jaganmohan Chandrasekaran Erin Lanus Laura J. Freeman Jeremy Werner 10 3 0 06 Oct 2023
Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning Harsh Chaudhari Giorgio Severi Alina Oprea Jonathan R. Ullman 23 5 0 05 Oct 2023
Coupling public and private gradient provably helps optimization Ruixuan Liu Zhiqi Bu Yu-Xiang Wang Sheng Zha George Karypis 10 2 0 02 Oct 2023
Building Privacy-Preserving and Secure Geospatial Artificial Intelligence Foundation Models Jinmeng Rao Song Gao Gengchen Mai Joanna M. Wardlaw 13 19 0 29 Sep 2023
Leave-one-out Distinguishability in Machine Learning Jiayuan Ye Anastasia Borovykh Soufiane Hayou Reza Shokri 20 8 0 29 Sep 2023
Understanding Deep Gradient Leakage via Inversion Influence Functions Haobo Zhang Junyuan Hong Yuyang Deng M. Mahdavi Jiayu Zhou FedML 40 6 0 22 Sep 2023
Communication Efficient Private Federated Learning Using Dithering Burak Hasircioglu Deniz Gunduz FedML 21 7 0 14 Sep 2023
Can Neural Network Memorization Be Localized? Pratyush Maini Michael C. Mozer Hanie Sedghi Zachary Chase Lipton J. Zico Kolter Chiyuan Zhang TDI 31 45 0 18 Jul 2023
Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses G. Buzaglo Niv Haim Gilad Yehudai Gal Vardi Yakir Oz Yaniv Nikankin Michal Irani 24 10 0 04 Jul 2023
Gaussian Membership Inference Privacy Tobias Leemann Martin Pawelczyk Gjergji Kasneci 13 14 0 12 Jun 2023
Learning a Neuron by a Shallow ReLU Network: Dynamics and Implicit Bias for Correlated Inputs D. Chistikov Matthias Englert R. Lazic MLT 32 12 0 10 Jun 2023
Revealing Model Biases: Assessing Deep Neural Networks via Recovered Sample Analysis M. Mehmanchi Mahbod Nouri Mohammad Sabokrou AAML 19 1 0 10 Jun 2023
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning Junyi Zhu Ruicong Yao Matthew B. Blaschko FedML 8 9 0 31 May 2023
Collaborative Learning via Prediction Consensus Dongyang Fan Celestine Mendler-Dünner Martin Jaggi FedML 20 7 0 29 May 2023
Training Data Extraction From Pre-trained Language Models: A Survey Shotaro Ishihara 24 46 0 25 May 2023
Differentially Private Synthetic Data via Foundation Model APIs 1: Images Zi-Han Lin Sivakanth Gopi Janardhan Kulkarni Harsha Nori Sergey Yekhanin 25 36 0 24 May 2023
Fantastic DNN Classifiers and How to Identify them without Data Nathaniel R. Dean D. Sarkar 21 1 0 24 May 2023
Can Copyright be Reduced to Privacy? N. Elkin-Koren Uri Y. Hacohen Roi Livni Shay Moran 6 21 0 24 May 2023
Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right? Hasan Hammoud Ameya Prabhu Ser-Nam Lim Philip H. S. Torr Adel Bibi Bernard Ghanem CLL 97 16 0 16 May 2023
Reconstructing Training Data from Multiclass Neural Networks G. Buzaglo Niv Haim Gilad Yehudai Gal Vardi Michal Irani 17 4 0 05 May 2023
Have it your way: Individualized Privacy Assignment for DP-SGD Franziska Boenisch Christopher Muhl Adam Dziedzic Roy Rinberg Nicolas Papernot 8 17 0 29 Mar 2023
Computationally Budgeted Continual Learning: What Does Matter? Ameya Prabhu Hasan Hammoud P. Dokania Philip H. S. Torr Ser-Nam Lim Bernard Ghanem Adel Bibi CLL 23 61 0 20 Mar 2023
The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks Spencer Frei Gal Vardi Peter L. Bartlett Nathan Srebro 27 17 0 02 Mar 2023
Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Linear Subspaces Odelia Melamed Gilad Yehudai Gal Vardi GAN 13 1 0 01 Mar 2023
Bounding Training Data Reconstruction in DP-SGD Jamie Hayes Saeed Mahloujifar Borja Balle AAML FedML 13 39 0 14 Feb 2023
One-shot Empirical Privacy Estimation for Federated Learning Galen Andrew Peter Kairouz Sewoong Oh Alina Oprea H. B. McMahan Vinith M. Suriyakumar FedML 11 32 0 06 Feb 2023
Private, fair and accurate: Training large-scale, privacy-preserving AI models in medical imaging Soroosh Tayebi Arasteh Alexander Ziller Christiane Kuhl Marcus R. Makowski S. Nebelung R. Braren Daniel Rueckert Daniel Truhn Georgios Kaissis MedIm 14 17 0 03 Feb 2023
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation Noel Loo Ramin Hasani Mathias Lechner Alexander Amini Daniela Rus DD 22 5 0 02 Feb 2023
Taming Normalizing Flows Shimon Malnick S. Avidan Ohad Fried TPM DiffM 6 1 0 29 Nov 2022
Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy Daphne Ippolito Florian Tramèr Milad Nasr Chiyuan Zhang Matthew Jagielski Katherine Lee Christopher A. Choquette-Choo Nicholas Carlini PILM MU 18 58 0 31 Oct 2022
Differentially Private Optimization on Large Model at Small Cost Zhiqi Bu Yu-Xiang Wang Sheng Zha George Karypis 22 52 0 30 Sep 2022
Differentially Private Bias-Term Fine-tuning of Foundation Models Zhiqi Bu Yu-Xiang Wang Sheng Zha George Karypis 10 46 0 30 Sep 2022
Learn the Time to Learn: Replay Scheduling in Continual Learning Marcus Klasson Hedvig Kjellström Chen Zhang CLL 13 9 0 18 Sep 2022
On the Implicit Bias in Deep-Learning Algorithms Gal Vardi FedML AI4CE 25 72 0 26 Aug 2022
On Margin Maximization in Linear and ReLU Networks Gal Vardi Ohad Shamir Nathan Srebro 40 27 0 06 Oct 2021
The Threat of Offensive AI to Organizations Yisroel Mirsky Ambra Demontis J. Kotak Ram Shankar Deng Gelei Liu Yang X. Zhang Wenke Lee Yuval Elovici Battista Biggio 25 81 0 30 Jun 2021
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 267 1,798 0 14 Dec 2020
When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning? Gavin Brown Mark Bun Vitaly Feldman Adam D. Smith Kunal Talwar 245 80 0 11 Dec 2020
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 185 357 0 24 Mar 2020
Cryptanalytic Extraction of Neural Network Models Nicholas Carlini Matthew Jagielski Ilya Mironov FedML MLAU MIACV AAML 65 134 0 10 Mar 2020