When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning?

11 December 2020

Papers citing "When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning?"

31 / 31 papers shown

Title
Undesirable Memorization in Large Language Models: A Survey Ali Satvaty Suzan Verberne Fatih Turkmen ELM PILM 71 7 0 03 Oct 2024
Range Membership Inference Attacks Jiashu Tao Reza Shokri 42 1 0 09 Aug 2024
A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks Hengzhu Liu Ping Xiong Tianqing Zhu Philip S. Yu 32 6 0 10 Jun 2024
Data Reconstruction: When You See It and When You Don't Edith Cohen Haim Kaplan Yishay Mansour Shay Moran Kobbi Nissim Uri Stemmer Eliad Tsfadia AAML 42 2 0 24 May 2024
Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses G. Buzaglo Niv Haim Gilad Yehudai Gal Vardi Yakir Oz Yaniv Nikankin Michal Irani 28 10 0 04 Jul 2023
Memory-Query Tradeoffs for Randomized Convex Optimization X. Chen Binghui Peng 36 6 0 21 Jun 2023
AI Model Disgorgement: Methods and Choices Alessandro Achille Michael Kearns Carson Klingenberg Stefano Soatto MU 23 11 0 07 Apr 2023
On Differential Privacy and Adaptive Data Analysis with Bounded Space Itai Dinur Uri Stemmer David P. Woodruff Samson Zhou 16 12 0 11 Feb 2023
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation Noel Loo Ramin Hasani Mathias Lechner Alexander Amini Daniela Rus DD 34 5 0 02 Feb 2023
Leveraging Unlabeled Data to Track Memorization Mahsa Forouzesh Hanie Sedghi Patrick Thiran NoLa TDI 34 3 0 08 Dec 2022
Verifiable and Provably Secure Machine Unlearning Thorsten Eisenhofer Doreen Riepel Varun Chandrasekaran Esha Ghosh O. Ohrimenko Nicolas Papernot AAML MU 33 26 0 17 Oct 2022
Understanding Transformer Memorization Recall Through Idioms Adi Haviv Ido Cohen Jacob Gidron R. Schuster Yoav Goldberg Mor Geva 28 48 0 07 Oct 2022
On the Impossible Safety of Large AI Models El-Mahdi El-Mhamdi Sadegh Farhadkhani R. Guerraoui Nirupam Gupta L. Hoang Rafael Pinot Sébastien Rouault John Stephan 30 31 0 30 Sep 2022
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics Shoaib Ahmed Siddiqui Nitarshan Rajkumar Tegan Maharaj David M. Krueger Sara Hooker 37 27 0 20 Sep 2022
The Privacy Onion Effect: Memorization is Relative Nicholas Carlini Matthew Jagielski Chiyuan Zhang Nicolas Papernot Andreas Terzis Florian Tramèr PILM MIACV 33 99 0 21 Jun 2022
Reconstructing Training Data from Trained Neural Networks Niv Haim Gal Vardi Gilad Yehudai Ohad Shamir Michal Irani 40 132 0 15 Jun 2022
Offline Reinforcement Learning with Differential Privacy Dan Qiao Yu-Xiang Wang OffRL 36 23 0 02 Jun 2022
Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models Kushal Tirumala Aram H. Markosyan Luke Zettlemoyer Armen Aghajanyan TDI 26 185 0 22 May 2022
Memory Bounds for Continual Learning Xi Chen Christos H. Papadimitriou Binghui Peng CLL LRM 27 22 0 22 Apr 2022
Deduplicating Training Data Mitigates Privacy Risks in Language Models Nikhil Kandpal Eric Wallace Colin Raffel PILM MU 28 274 0 14 Feb 2022
Deletion Inference, Reconstruction, and Compliance in Machine (Un)Learning Ji Gao Sanjam Garg Mohammad Mahmoody Prashant Nalini Vasudevan MIACV AAML 19 22 0 07 Feb 2022
Datamodels: Predicting Predictions from Training Data Andrew Ilyas Sung Min Park Logan Engstrom Guillaume Leclerc A. Madry TDI 38 130 0 01 Feb 2022
Reconstructing Training Data with Informed Adversaries Borja Balle Giovanni Cherubin Jamie Hayes MIACV AAML 35 158 0 13 Jan 2022
Membership Inference Attacks From First Principles Nicholas Carlini Steve Chien Milad Nasr Shuang Song Andreas Terzis Florian Tramèr MIACV MIALM 24 639 0 07 Dec 2021
What Do We Mean by Generalization in Federated Learning? Honglin Yuan Warren Morningstar Lin Ning K. Singhal OOD FedML 35 71 0 27 Oct 2021
Differentially Private Fine-tuning of Language Models Da Yu Saurabh Naik A. Backurs Sivakanth Gopi Huseyin A. Inan ... Y. Lee Andre Manoel Lukas Wutschitz Sergey Yekhanin Huishuai Zhang 134 346 0 13 Oct 2021
Large-Scale Differentially Private BERT Rohan Anil Badih Ghazi Vineet Gupta Ravi Kumar Pasin Manurangsi 33 131 0 03 Aug 2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation Gavin Brown Marco Gaboardi Adam D. Smith Jonathan R. Ullman Lydia Zakynthinou FedML 28 48 0 24 Jun 2021
Membership Inference on Word Embedding and Beyond Saeed Mahloujifar Huseyin A. Inan Melissa Chase Esha Ghosh Marcello Hasegawa MIACV SILM 19 46 0 21 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 290 1,814 0 14 Dec 2020
Sample Complexity Bounds on Differentially Private Learning via Communication Complexity Vitaly Feldman David Xiao 169 71 0 25 Feb 2014