POUR: A Provably Optimal Method for Unlearning Representations via Neural Collapse

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Le, Anjie, Peng, Can, Liu, Yuyuan, Noble, J. Alison
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Neural Collapse-Inspired Multi-Label Federated Learning under Label-Distribution Skew
by: Peng, Can, et al.
Published: (2025)

Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning
by: Liu, Yuyuan, et al.
Published: (2026)

From Failure to Feedback: Group Revision Unlocks Hard Cases in Object-Level Grounding
by: Liu, Yuyuan, et al.
Published: (2026)

Enhancing targeted transferability via feature space fine-tuning
by: Zeng, Hui, et al.
Published: (2024)

F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics
by: Saha, Pramit, et al.
Published: (2024)

MMSummary: Multimodal Summary Generation for Fetal Ultrasound Video
by: Guo, Xiaoqing, et al.
Published: (2024)

Federated Continual 3D Segmentation With Single-round Communication
by: Peng, Can, et al.
Published: (2025)

CURE: Concept Unlearning via Orthogonal Representation Editing in Diffusion Models
by: Biswas, Shristi Das, et al.
Published: (2025)

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

Client-Level Differential Privacy via Adaptive Intermediary in Federated Medical Imaging
by: Jiang, Meirui, et al.
Published: (2023)

Neural Geometry Image-Based Representations with Optimal Transport (OT)
by: Gao, Xiang, et al.
Published: (2025)

ItTakesTwo: Leveraging Peer Representations for Semi-supervised LiDAR Semantic Segmentation
by: Liu, Yuyuan, et al.
Published: (2024)

Controllable Unlearning for Image-to-Image Generative Models via $\varepsilon$-Constrained Optimization
by: Feng, Xiaohua, et al.
Published: (2024)

Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representations
by: Chobola, Tomáš, et al.
Published: (2024)

AuralSAM2: Enabling SAM2 Hear Through Pyramid Audio-Visual Feature Prompting
by: Liu, Yuyuan, et al.
Published: (2025)

Neural Collapse in Test-Time Adaptation
by: Chen, Xiao, et al.
Published: (2025)

Neural Collapse Inspired Knowledge Distillation
by: Zhang, Shuoxi, et al.
Published: (2024)

Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography
by: Yang, Yingyu, et al.
Published: (2026)

Unlearning Backdoor Threats: Enhancing Backdoor Defense in Multimodal Contrastive Learning via Local Token Unlearning
by: Liang, Siyuan, et al.
Published: (2024)

Suppression or Deletion: A Restoration-Based Representation-Level Analysis of Machine Unlearning
by: Jang, Yurim, et al.
Published: (2026)

MedCutMix: A Data-Centric Approach to Improve Radiology Vision-Language Pre-training with Disease Awareness
by: Wang, Sinuo, et al.
Published: (2025)

Two Heads Are Better Than One: Averaging along Fine-Tuning to Improve Targeted Transferability
by: Zeng, Hui, et al.
Published: (2024)

Unlearning for One-Step Generative Models via Unbalanced Optimal Transport
by: Choi, Hyundo, et al.
Published: (2026)

Self-supervised Learning of Echocardiographic Video Representations via Online Cluster Distillation
by: Mishra, Divyanshu, et al.
Published: (2025)

Cluster-Aware Neural Collapse Prompt Tuning for Long-Tailed Generalization of Vision-Language Models
by: Guo, Boyang, et al.
Published: (2026)

Knowledge Swapping via Learning and Unlearning
by: Xing, Mingyu, et al.
Published: (2025)

On the Provable Importance of Gradients for Language-Assisted Image Clustering
by: Peng, Bo, et al.
Published: (2025)

Evaluating the Fairness of Neural Collapse in Medical Image Classification
by: Mouheb, Kaouther, et al.
Published: (2024)

Learning to learn skill assessment for fetal ultrasound scanning
by: Wang, Yipei, et al.
Published: (2025)

UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models
by: Zhang, Yihua, et al.
Published: (2024)

MUNBa: Machine Unlearning via Nash Bargaining
by: Wu, Jing, et al.
Published: (2024)

Decoupled Distillation to Erase: A General Unlearning Method for Any Class-centric Tasks
by: Zhou, Yu, et al.
Published: (2025)

Concept Unlearning by Modeling Key Steps of Diffusion Process
by: Zhang, Chaoshuo, et al.
Published: (2025)

Neural Spatial-Temporal Tensor Representation for Infrared Small Target Detection
by: Wu, Fengyi, et al.
Published: (2024)

This Looks Distinctly Like That: Grounding Interpretable Recognition in Stiefel Geometry against Neural Collapse
by: Jia, Junhao, et al.
Published: (2026)

Enhancing Adversarial Transferability via Component-Wise Transformation
by: Liu, Hangyu, et al.
Published: (2025)

Beyond Modality Collapse: Representations Blending for Multimodal Dataset Distillation
by: Zhang, Xin, et al.
Published: (2025)

Bridging Generative and Discriminative Noisy-Label Learning via Direction-Agnostic EM Formulation
by: Liu, Fengbei, et al.
Published: (2023)

Video Unlearning via Low-Rank Refusal Vector
by: Facchiano, Simone, et al.
Published: (2025)

Hierarchical Neural Collapse Detection Transformer for Class Incremental Object Detection
by: Pham, Duc Thanh, et al.
Published: (2025)