Saved in:
| Main Authors: | Sha, Alyssa Shuang, Nunes, Bernardo Pereira, Haller, Armin |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2405.20620 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Continual Learning for VLMs: A Survey and Taxonomy Beyond Forgetting
by: Liu, Yuyang, et al.
Published: (2025)
by: Liu, Yuyang, et al.
Published: (2025)
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
by: Wang, Zhenyi, et al.
Published: (2023)
by: Wang, Zhenyi, et al.
Published: (2023)
Towards Reliable Forgetting: A Survey on Machine Unlearning Verification
by: Xue, Lulu, et al.
Published: (2025)
by: Xue, Lulu, et al.
Published: (2025)
Evolving Machine Learning in Non-Stationary Environments: A Unified Survey of Drift, Forgetting, and Adaptation
by: Martin, Ignacio Cabrera, et al.
Published: (2025)
by: Martin, Ignacio Cabrera, et al.
Published: (2025)
A Survey on Data Quality Dimensions and Tools for Machine Learning
by: Zhou, Yuhan, et al.
Published: (2024)
by: Zhou, Yuhan, et al.
Published: (2024)
Beyond Forgetting: Machine Unlearning Elicits Controllable Side Behaviors and Capabilities
by: Dang, Tien, et al.
Published: (2026)
by: Dang, Tien, et al.
Published: (2026)
Forgetting Has Neighbors: Localized Collateral Forgetting in Machine Unlearning
by: Dolgova, Polina, et al.
Published: (2026)
by: Dolgova, Polina, et al.
Published: (2026)
Machine Unlearning for Streaming Forgetting
by: Shen, Shaofei, et al.
Published: (2025)
by: Shen, Shaofei, et al.
Published: (2025)
Machine Unlearning under Retain-Forget Entanglement
by: Cheng, Jingpu, et al.
Published: (2026)
by: Cheng, Jingpu, et al.
Published: (2026)
Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond
by: Li, Qiongxiu, et al.
Published: (2025)
by: Li, Qiongxiu, et al.
Published: (2025)
Do Neural Operators Forget Geometry? The Forgetting Hypothesis in Deep Operator Learning
by: Xia, Yanming, et al.
Published: (2026)
by: Xia, Yanming, et al.
Published: (2026)
Continual Learning with Strategic Selection and Forgetting for Network Intrusion Detection
by: Zhang, Xinchen, et al.
Published: (2024)
by: Zhang, Xinchen, et al.
Published: (2024)
Forget Forgetting: Continual Learning in a World of Abundant Memory
by: Cho, Dongkyu, et al.
Published: (2025)
by: Cho, Dongkyu, et al.
Published: (2025)
Fairness in Machine Learning: A Survey
by: Caton, Simon, et al.
Published: (2020)
by: Caton, Simon, et al.
Published: (2020)
Towards Aligned Data Forgetting via Twin Machine Unlearning
by: Niu, Zhenxing, et al.
Published: (2025)
by: Niu, Zhenxing, et al.
Published: (2025)
Is Gradient Ascent Really Necessary? Memorize to Forget for Machine Unlearning
by: Huang, Zhuo, et al.
Published: (2026)
by: Huang, Zhuo, et al.
Published: (2026)
Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning
by: Fan, Chongyu, et al.
Published: (2024)
by: Fan, Chongyu, et al.
Published: (2024)
Forget-MI: Machine Unlearning for Forgetting Multimodal Information in Healthcare Settings
by: Hardan, Shahad, et al.
Published: (2025)
by: Hardan, Shahad, et al.
Published: (2025)
Beyond Anti-Forgetting: Multimodal Continual Instruction Tuning with Positive Forward Transfer
by: Zheng, Junhao, et al.
Published: (2024)
by: Zheng, Junhao, et al.
Published: (2024)
Enhanced Prediction of Ventilator-Associated Pneumonia in Patients with Traumatic Brain Injury Using Advanced Machine Learning Techniques
by: Ashrafi, Negin, et al.
Published: (2024)
by: Ashrafi, Negin, et al.
Published: (2024)
When to Forget? Complexity Trade-offs in Machine Unlearning
by: Van Waerebeke, Martin, et al.
Published: (2025)
by: Van Waerebeke, Martin, et al.
Published: (2025)
Rethinking Machine Unlearning: Models Designed to Forget via Key Deletion
by: Laguna, Sonia, et al.
Published: (2026)
by: Laguna, Sonia, et al.
Published: (2026)
A Survey on Fairness for Machine Learning on Graphs
by: Laclau, Charlotte, et al.
Published: (2022)
by: Laclau, Charlotte, et al.
Published: (2022)
Curriculum Graph Machine Learning: A Survey
by: Li, Haoyang, et al.
Published: (2023)
by: Li, Haoyang, et al.
Published: (2023)
No Forgetting Learning: Buffer-free Continual Learning Classification
by: Vahedifar, Mohammad Ali, et al.
Published: (2025)
by: Vahedifar, Mohammad Ali, et al.
Published: (2025)
Understanding Forgetting in Continual Learning with Linear Regression
by: Ding, Meng, et al.
Published: (2024)
by: Ding, Meng, et al.
Published: (2024)
Understanding Generalization and Forgetting in In-Context Continual Learning
by: Li, Guangyu, et al.
Published: (2026)
by: Li, Guangyu, et al.
Published: (2026)
Spurious Forgetting in Continual Learning of Language Models
by: Zheng, Junhao, et al.
Published: (2025)
by: Zheng, Junhao, et al.
Published: (2025)
Forgetting Similar Samples: Can Machine Unlearning Do it Better?
by: Xu, Heng, et al.
Published: (2026)
by: Xu, Heng, et al.
Published: (2026)
Machine Unlearning using Forgetting Neural Networks
by: Hatua, Amartya, et al.
Published: (2024)
by: Hatua, Amartya, et al.
Published: (2024)
Forgetting is Everywhere
by: Sanati, Ben, et al.
Published: (2025)
by: Sanati, Ben, et al.
Published: (2025)
Absolute Evaluation Measures for Machine Learning: A Survey
by: Beddar-Wiesing, Silvia, et al.
Published: (2025)
by: Beddar-Wiesing, Silvia, et al.
Published: (2025)
Neural Garbage Collection: Learning to Forget while Learning to Reason
by: Li, Michael Y., et al.
Published: (2026)
by: Li, Michael Y., et al.
Published: (2026)
A Survey on Cell Nuclei Instance Segmentation and Classification: Leveraging Context and Attention
by: Nunes, João D., et al.
Published: (2024)
by: Nunes, João D., et al.
Published: (2024)
Beyond Reasoning Gains: Mitigating General Capabilities Forgetting in Large Reasoning Models
by: Phan, Hoang, et al.
Published: (2025)
by: Phan, Hoang, et al.
Published: (2025)
Optimizing Mortality Prediction for ICU Heart Failure Patients: Leveraging XGBoost and Advanced Machine Learning with the MIMIC-III Database
by: Ashrafi, Negin, et al.
Published: (2024)
by: Ashrafi, Negin, et al.
Published: (2024)
From Tiny Machine Learning to Tiny Deep Learning: A Survey
by: Somvanshi, Shriyank, et al.
Published: (2025)
by: Somvanshi, Shriyank, et al.
Published: (2025)
Learning Curves for Decision Making in Supervised Machine Learning: A Survey
by: Mohr, Felix, et al.
Published: (2022)
by: Mohr, Felix, et al.
Published: (2022)
Data-dependent and Oracle Bounds on Forgetting in Continual Learning
by: Friedman, Lior, et al.
Published: (2024)
by: Friedman, Lior, et al.
Published: (2024)
Eidetic Learning: an Efficient and Provable Solution to Catastrophic Forgetting
by: Dronen, Nicholas, et al.
Published: (2025)
by: Dronen, Nicholas, et al.
Published: (2025)
Similar Items
-
Continual Learning for VLMs: A Survey and Taxonomy Beyond Forgetting
by: Liu, Yuyang, et al.
Published: (2025) -
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
by: Wang, Zhenyi, et al.
Published: (2023) -
Towards Reliable Forgetting: A Survey on Machine Unlearning Verification
by: Xue, Lulu, et al.
Published: (2025) -
Evolving Machine Learning in Non-Stationary Environments: A Unified Survey of Drift, Forgetting, and Adaptation
by: Martin, Ignacio Cabrera, et al.
Published: (2025) -
A Survey on Data Quality Dimensions and Tools for Machine Learning
by: Zhou, Yuhan, et al.
Published: (2024)