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2012.06421
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When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning?
Symposium on the Theory of Computing (STOC), 2020
11 December 2020
Gavin Brown
Mark Bun
Vitaly Feldman
Adam D. Smith
Kunal Talwar
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Papers citing
"When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning?"
50 / 92 papers shown
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Efficiently Attacking Memorization Scores
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Synth-MIA: A Testbed for Auditing Privacy Leakage in Tabular Data Synthesis
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Access Paths for Efficient Ordering with Large Language Models
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Jiayue Chen
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Unveiling Over-Memorization in Finetuning LLMs for Reasoning Tasks
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A Common Pool of Privacy Problems: Legal and Technical Lessons from a Large-Scale Web-Scraped Machine Learning Dataset
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Jevan Hutson
William Agnew
Imaad Huda
Tadayoshi Kohno
Jamie Morgenstern
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391
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Nicolás Berrios
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276
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Memorization in Language Models through the Lens of Intrinsic Dimension
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364
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Trade-offs in Data Memorization via Strong Data Processing Inequalities
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451
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423
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268
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219
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Jongwon Jeong
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324
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07 Apr 2025
Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond
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Xiaoyu Luo
Yiyi Chen
Johannes Bjerva
565
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10 Mar 2025
Machine Learners Should Acknowledge the Legal Implications of Large Language Models as Personal Data
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Michèle Finck
Kristof Meding
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488
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03 Mar 2025
The Pitfalls of Memorization: When Memorization Hurts Generalization
International Conference on Learning Representations (ICLR), 2024
Reza Bayat
Mohammad Pezeshki
Elvis Dohmatob
David Lopez-Paz
Pascal Vincent
OOD
362
16
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10 Dec 2024
Improved Localized Machine Unlearning Through the Lens of Memorization
Reihaneh Torkzadehmahani
Reza Nasirigerdeh
Georgios Kaissis
Daniel Rueckert
Gintare Karolina Dziugaite
Eleni Triantafillou
MU
219
7
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03 Dec 2024
Slowing Down Forgetting in Continual Learning
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Tobias Schlagenhauf
Stefan Feuerriegel
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456
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Undesirable Memorization in Large Language Models: A Survey
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Range Membership Inference Attacks
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Reza Shokri
472
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Demystifying Verbatim Memorization in Large Language Models
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Diyi Yang
Christopher Potts
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338
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25 Jul 2024
A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks
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Hengzhu Liu
Ping Xiong
Tianqing Zhu
Philip S. Yu
248
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Data Reconstruction: When You See It and When You Don't
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Haim Kaplan
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Eliad Tsfadia
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315
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Exploring prompts to elicit memorization in masked language model-based named entity recognition
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Anastasiia Sedova
Pedro Henrique Luz de Araujo
Vasiliki Kougia
Lisa Nussbaumer
Benjamin Roth
296
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05 May 2024
Differentially Private Reinforcement Learning with Self-Play
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Yu Wang
274
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11 Apr 2024
Gradient Descent is Pareto-Optimal in the Oracle Complexity and Memory Tradeoff for Feasibility Problems
IEEE Annual Symposium on Foundations of Computer Science (FOCS), 2024
Moise Blanchard
265
1
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10 Apr 2024
Unveiling Privacy, Memorization, and Input Curvature Links
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Efstathia Soufleri
Abolfazl Hashemi
Kaushik Roy
305
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Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization
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Mahdi Haghifam
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Daniel M. Roy
360
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Do LLMs Dream of Ontologies?
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Paolo Fiorini
Simone Paolo Ponzetto
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367
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26 Jan 2024
Memorization in Self-Supervised Learning Improves Downstream Generalization
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Muhammad Ahmad Kaleem
Adam Dziedzic
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Nicolas Papernot
Franziska Boenisch
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429
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The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright Breaches Without Adjusting Finetuning Pipeline
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Qianli Shen
Yao Tong
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SoK: Unintended Interactions among Machine Learning Defenses and Risks
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S. Szyller
Nadarajah Asokan
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384
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Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates
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Enayat Ullah
Raman Arora
Raef Bassily
Cristóbal Guzmán
343
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Joshua Robinson
Ollie Liu
Isabelle Lee
Dani Yogatama
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227
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Privacy Threats in Stable Diffusion Models
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Charles Fleming
Charles Walter
211
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SoK: Memorisation in machine learning
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Moritz Knolle
Georgios Kaissis
333
1
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Why Train More? Effective and Efficient Membership Inference via Memorization
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Shruti Tople
Varun Chandrasekaran
Somesh Jha
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276
3
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What do larger image classifiers memorise?
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A. Menon
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Anonymous Learning via Look-Alike Clustering: A Precise Analysis of Model Generalization
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434
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Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses
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Deconstructing Classifiers: Towards A Data Reconstruction Attack Against Text Classification Models
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326
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Memory-Query Tradeoffs for Randomized Convex Optimization
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240
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Machine Unlearning: A Survey
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282
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TMI! Finetuned Models Leak Private Information from their Pretraining Data
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Seanie Lee
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Private Everlasting Prediction
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AI Model Disgorgement: Methods and Choices
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Michael Kearns
Carson Klingenberg
Stefano Soatto
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