:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Hatua, Amartya, Nguyen, Trung T., Sung, Andrew H.
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2407.18467
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Machine Unlearning using Forgetting Neural Networks
by: Hatua, Amartya, et al.
Published: (2024)

Mechanistic Interpretability of GPT-2: Lexical and Contextual Layers in Sentiment Analysis
by: Hatua, Amartya
Published: (2025)

A Survey of Machine Unlearning
by: Nguyen, Thanh Tam, et al.
Published: (2022)

Online Learning and Unlearning
by: Hu, Yaxi, et al.
Published: (2025)

Corrective Machine Unlearning
by: Goel, Shashwat, et al.
Published: (2024)

Less Noise, Same Certificate: Retain Sensitivity for Unlearning
by: Heinzler, Carolin, et al.
Published: (2026)

Attribute-to-Delete: Machine Unlearning via Datamodel Matching
by: Georgiev, Kristian, et al.
Published: (2024)

FairFinGAN: Fairness-aware Synthetic Financial Data Generation
by: Quy, Tai Le, et al.
Published: (2026)

Example-based Explanations for Random Forests using Machine Unlearning
by: Surve, Tanmay, et al.
Published: (2024)

Multi-Objective Reference-Aligned Machine Unlearning
by: Khosrowshahli, Rasa, et al.
Published: (2026)

Optimizing Multi-Stage Language Models for Effective Text Retrieval
by: Trung, Quang Hoang, et al.
Published: (2024)

Open Problems in Machine Unlearning for AI Safety
by: Barez, Fazl, et al.
Published: (2025)

Beyond Forgetting: Machine Unlearning Elicits Controllable Side Behaviors and Capabilities
by: Dang, Tien, et al.
Published: (2026)

Model Sparsity Can Simplify Machine Unlearning
by: Jia, Jinghan, et al.
Published: (2023)

FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning
by: Shaik, Thanveer, et al.
Published: (2023)

An Illusion of Unlearning? Assessing Machine Unlearning Through Internal Representations
by: Gao, Yichen, et al.
Published: (2026)

FUNU: Boosting Machine Unlearning Efficiency by Filtering Unnecessary Unlearning
by: Li, Zitong, et al.
Published: (2025)

Gap Safe Screening Rules for Fast Training of Robust Support Vector Machines under Feature Noise
by: Nguyen, Tan-Hau, et al.
Published: (2026)

Diffusion-based Negative Sampling on Graphs for Link Prediction
by: Nguyen, Trung-Kien, et al.
Published: (2024)

A Review on Machine Unlearning
by: Zhang, Haibo, et al.
Published: (2024)

Towards Natural Machine Unlearning
by: He, Zhengbao, et al.
Published: (2024)

Reference-Guided Machine Unlearning
by: Mirlach, Jonas, et al.
Published: (2026)

Machine Unlearning for Streaming Forgetting
by: Shen, Shaofei, et al.
Published: (2025)

Sharpness-Aware Machine Unlearning
by: Tang, Haoran, et al.
Published: (2025)

Fairness and Robustness in Machine Unlearning
by: Tran, Khoa, et al.
Published: (2025)

Adversarial Machine Unlearning
by: Di, Zonglin, et al.
Published: (2024)

Exploring the Precise Dynamics of Single-Layer GAN Models: Leveraging Multi-Feature Discriminators for High-Dimensional Subspace Learning
by: Bond, Andrew, et al.
Published: (2024)

Deep Unlearn: Benchmarking Machine Unlearning for Image Classification
by: Cadet, Xavier F., et al.
Published: (2024)

Contrastive Unlearning: A Contrastive Approach to Machine Unlearning
by: Lee, Hong kyu, et al.
Published: (2024)

Rethinking Machine Unlearning for Large Language Models
by: Liu, Sijia, et al.
Published: (2024)

Towards Irreversible Machine Unlearning for Diffusion Models
by: Yuan, Xun, et al.
Published: (2025)

Toward a Flexible Framework for Linear Representation Hypothesis Using Maximum Likelihood Estimation
by: Nguyen, Trung, et al.
Published: (2025)

Delta-Influence: Unlearning Poisons via Influence Functions
by: Li, Wenjie, et al.
Published: (2024)

Erase at the Core: Representation Unlearning for Machine Unlearning
by: Lee, Jaewon, et al.
Published: (2026)

Unlearning's Blind Spots: Over-Unlearning and Prototypical Relearning Attack
by: Ha, SeungBum, et al.
Published: (2025)

WIN-U: Woodbury-Informed Newton-Unlearning as a retain-free Machine Unlearning Framework
by: Zhao, Xingjian, et al.
Published: (2026)

Fast-FedUL: A Training-Free Federated Unlearning with Provable Skew Resilience
by: Huynh, Thanh Trung, et al.
Published: (2024)

MultiDelete for Multimodal Machine Unlearning
by: Cheng, Jiali, et al.
Published: (2023)

Efficient Machine Unlearning by Model Splitting and Core Sample Selection
by: Egger, Maximilian, et al.
Published: (2025)

Multi-FinGAN: Generative Coarse-To-Fine Sampling of Multi-Finger Grasps
by: Lundell, Jens, et al.
Published: (2020)