Improved Localized Machine Unlearning Through the Lens of Memorization
Fuente:
arXiv
Saved in:
| Main Authors: | Torkzadehmahani, Reihaneh, Nasirigerdeh, Reza, Kaissis, Georgios, Rueckert, Daniel, Dziugaite, Gintare Karolina, Triantafillou, Eleni |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Kernel Normalized Convolutional Networks
by: Nasirigerdeh, Reza, et al.
Published: (2022)
by: Nasirigerdeh, Reza, et al.
Published: (2022)
Data Selection for Transfer Unlearning
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2024)
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2024)
Machine Unlearning for Medical Imaging
by: Nasirigerdeh, Reza, et al.
Published: (2024)
by: Nasirigerdeh, Reza, et al.
Published: (2024)
Leveraging Per-Instance Privacy for Machine Unlearning
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2025)
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2025)
From Dormant to Deleted: Tamper-Resistant Unlearning Through Weight-Space Regularization
by: Siddiqui, Shoaib Ahmed, et al.
Published: (2025)
by: Siddiqui, Shoaib Ahmed, et al.
Published: (2025)
Mechanistic Unlearning: Robust Knowledge Unlearning and Editing via Mechanistic Localization
by: Guo, Phillip, et al.
Published: (2024)
by: Guo, Phillip, et al.
Published: (2024)
Detoxifying LLMs via Representation Erasure-Based Preference Optimization
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2026)
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2026)
Laplace Sample Information: Data Informativeness Through a Bayesian Lens
by: Kaiser, Johannes, et al.
Published: (2025)
by: Kaiser, Johannes, et al.
Published: (2025)
The Non-Local Model Merging Problem: Permutation Symmetries and Variance Collapse
by: Sharma, Ekansh, et al.
Published: (2024)
by: Sharma, Ekansh, et al.
Published: (2024)
Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization
by: Attias, Idan, et al.
Published: (2024)
by: Attias, Idan, et al.
Published: (2024)
Unlearning in- vs. out-of-distribution data in LLMs under gradient-based method
by: Baluta, Teodora, et al.
Published: (2024)
by: Baluta, Teodora, et al.
Published: (2024)
Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias
by: Yang, Yu, et al.
Published: (2023)
by: Yang, Yu, et al.
Published: (2023)
Less is More: Undertraining Experts Improves Model Upcycling
by: Horoi, Stefan, et al.
Published: (2025)
by: Horoi, Stefan, et al.
Published: (2025)
Your Privacy Depends on Others: Collusion Vulnerabilities in Individual Differential Privacy
by: Kaiser, Johannes, et al.
Published: (2026)
by: Kaiser, Johannes, et al.
Published: (2026)
ChEX: Interactive Localization and Region Description in Chest X-rays
by: Müller, Philip, et al.
Published: (2024)
by: Müller, Philip, et al.
Published: (2024)
How Much Is One Recurrence Worth? Iso-Depth Scaling Laws for Looped Language Models
by: Schwethelm, Kristian, et al.
Published: (2026)
by: Schwethelm, Kristian, et al.
Published: (2026)
Gradient-Weight Alignment as a Train-Time Proxy for Generalization in Classification Tasks
by: Hölzl, Florian A., et al.
Published: (2025)
by: Hölzl, Florian A., et al.
Published: (2025)
To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models
by: Barbulescu, George-Octavian, et al.
Published: (2024)
by: Barbulescu, George-Octavian, et al.
Published: (2024)
Incentivising the federation: gradient-based metrics for data selection and valuation in private decentralised training
by: Usynin, Dmitrii, et al.
Published: (2023)
by: Usynin, Dmitrii, et al.
Published: (2023)
Step-resolved data attribution for looped transformers
by: Kaissis, Georgios, et al.
Published: (2026)
by: Kaissis, Georgios, et al.
Published: (2026)
Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data
by: Inane, Ahmed Mehdi, et al.
Published: (2026)
by: Inane, Ahmed Mehdi, et al.
Published: (2026)
Dataset Difficulty and the Role of Inductive Bias
by: Kwok, Devin, et al.
Published: (2024)
by: Kwok, Devin, et al.
Published: (2024)
Leveraging Function Space Aggregation for Federated Learning at Scale
by: Dhawan, Nikita, et al.
Published: (2023)
by: Dhawan, Nikita, et al.
Published: (2023)
Is your algorithm unlearning or untraining?
by: Triantafillou, Eleni, et al.
Published: (2026)
by: Triantafillou, Eleni, et al.
Published: (2026)
Weakly Supervised Object Detection in Chest X-Rays with Differentiable ROI Proposal Networks and Soft ROI Pooling
by: Müller, Philip, et al.
Published: (2024)
by: Müller, Philip, et al.
Published: (2024)
Unintended Memorization of Sensitive Information in Fine-Tuned Language Models
by: Szep, Marton, et al.
Published: (2026)
by: Szep, Marton, et al.
Published: (2026)
Soup to go: mitigating forgetting during continual learning with model averaging
by: Kleiman, Anat, et al.
Published: (2025)
by: Kleiman, Anat, et al.
Published: (2025)
Redirection for Erasing Memory (REM): Towards a universal unlearning method for corrupted data
by: Schoepf, Stefan, et al.
Published: (2025)
by: Schoepf, Stefan, et al.
Published: (2025)
Simultaneous linear connectivity of neural networks modulo permutation
by: Sharma, Ekansh, et al.
Published: (2024)
by: Sharma, Ekansh, et al.
Published: (2024)
On Traceability in $\ell_p$ Stochastic Convex Optimization
by: Voitovych, Sasha, et al.
Published: (2025)
by: Voitovych, Sasha, et al.
Published: (2025)
Are we making progress in unlearning? Findings from the first NeurIPS unlearning competition
by: Triantafillou, Eleni, et al.
Published: (2024)
by: Triantafillou, Eleni, et al.
Published: (2024)
Evaluating Interventional Reasoning Capabilities of Large Language Models
by: Kasetty, Tejas, et al.
Published: (2024)
by: Kasetty, Tejas, et al.
Published: (2024)
Torque-Aware Momentum
by: Malviya, Pranshu, et al.
Published: (2024)
by: Malviya, Pranshu, et al.
Published: (2024)
Survival In-Context: Amortized Bayesian Survival Analysis via Prior-Fitted Networks
by: Seletkov, Dmitrii, et al.
Published: (2026)
by: Seletkov, Dmitrii, et al.
Published: (2026)
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy
by: Kaissis, Georgios, et al.
Published: (2024)
by: Kaissis, Georgios, et al.
Published: (2024)
Inexact Unlearning Needs More Careful Evaluations to Avoid a False Sense of Privacy
by: Hayes, Jamie, et al.
Published: (2024)
by: Hayes, Jamie, et al.
Published: (2024)
Efficient numeracy in language models through single-token number embeddings
by: Kreitner, Linus, et al.
Published: (2025)
by: Kreitner, Linus, et al.
Published: (2025)
Differentially Private Active Learning: Balancing Effective Data Selection and Privacy
by: Schwethelm, Kristian, et al.
Published: (2024)
by: Schwethelm, Kristian, et al.
Published: (2024)
Complex-valued Federated Learning with Differential Privacy and MRI Applications
by: Riess, Anneliese, et al.
Published: (2021)
by: Riess, Anneliese, et al.
Published: (2021)
SSFL: Discovering Sparse Unified Subnetworks at Initialization for Efficient Federated Learning
by: Ohib, Riyasat, et al.
Published: (2024)
by: Ohib, Riyasat, et al.
Published: (2024)
Similar Items
-
Kernel Normalized Convolutional Networks
by: Nasirigerdeh, Reza, et al.
Published: (2022) -
Data Selection for Transfer Unlearning
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2024) -
Machine Unlearning for Medical Imaging
by: Nasirigerdeh, Reza, et al.
Published: (2024) -
Leveraging Per-Instance Privacy for Machine Unlearning
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2025) -
From Dormant to Deleted: Tamper-Resistant Unlearning Through Weight-Space Regularization
by: Siddiqui, Shoaib Ahmed, et al.
Published: (2025)