Saved in:
| Main Authors: | Qureshi, Sadia, Shaik, Thanveer, Tao, Xiaohui, Xie, Haoran, Li, Lin, Yong, Jianming, Jia, Xiaohua |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.16708 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and Taxonomy
by: Shaik, Thanveer, et al.
Published: (2023)
by: Shaik, Thanveer, et al.
Published: (2023)
Graph-enabled Reinforcement Learning for Time Series Forecasting with Adaptive Intelligence
by: Shaik, Thanveer, et al.
Published: (2023)
by: Shaik, Thanveer, et al.
Published: (2023)
Adaptive Multi-Agent Deep Reinforcement Learning for Timely Healthcare Interventions
by: Shaik, Thanveer, et al.
Published: (2023)
by: Shaik, Thanveer, et al.
Published: (2023)
FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning
by: Shaik, Thanveer, et al.
Published: (2023)
by: Shaik, Thanveer, et al.
Published: (2023)
Quantum Machine Unlearning: Foundations, Mechanisms, and Taxonomy
by: Shaik, Thanveer, et al.
Published: (2025)
by: Shaik, Thanveer, et al.
Published: (2025)
Clustered FedStack: Intermediate Global Models with Bayesian Information Criterion
by: Shaik, Thanveer, et al.
Published: (2023)
by: Shaik, Thanveer, et al.
Published: (2023)
PDRL: Multi-Agent based Reinforcement Learning for Predictive Monitoring
by: Shaik, Thanveer, et al.
Published: (2023)
by: Shaik, Thanveer, et al.
Published: (2023)
Causal Neighbourhood Learning for Invariant Graph Representations
by: Job, Simi, et al.
Published: (2026)
by: Job, Simi, et al.
Published: (2026)
Machine Unlearning: Solutions and Challenges
by: Xu, Jie, et al.
Published: (2023)
by: Xu, Jie, et al.
Published: (2023)
Optimizing Graph Causal Classification Models: Estimating Causal Effects and Addressing Confounders
by: Job, Simi, et al.
Published: (2026)
by: Job, Simi, et al.
Published: (2026)
QXAI: Explainable AI Framework for Quantitative Analysis in Patient Monitoring Systems
by: Shaik, Thanveer, et al.
Published: (2023)
by: Shaik, Thanveer, et al.
Published: (2023)
LEGO: A Lightweight and Efficient Multiple-Attribute Unlearning Framework for Recommender Systems
by: Yu, Fengyuan, et al.
Published: (2025)
by: Yu, Fengyuan, et al.
Published: (2025)
LMEraser: Large Model Unlearning through Adaptive Prompt Tuning
by: Xu, Jie, et al.
Published: (2024)
by: Xu, Jie, et al.
Published: (2024)
Advancing Biomedicine with Graph Representation Learning: Recent Progress, Challenges, and Future Directions
by: Li, Fang, et al.
Published: (2023)
by: Li, Fang, et al.
Published: (2023)
eCIL-MU: Embedding based Class Incremental Learning and Machine Unlearning
by: Zuo, Zhiwei, et al.
Published: (2024)
by: Zuo, Zhiwei, et al.
Published: (2024)
A Neuro-inspired Interpretation of Unlearning in Large Language Models through Sample-level Unlearning Difficulty
by: Feng, Xiaohua, et al.
Published: (2025)
by: Feng, Xiaohua, et al.
Published: (2025)
Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement
by: Huang, Zhehao, et al.
Published: (2024)
by: Huang, Zhehao, et al.
Published: (2024)
A Survey on Context-Aware Multi-Agent Systems: Techniques, Challenges and Future Directions
by: Du, Hung, et al.
Published: (2024)
by: Du, Hung, et al.
Published: (2024)
Medical Multimodal Foundation Models in Clinical Diagnosis and Treatment: Applications, Challenges, and Future Directions
by: Sun, Kai, et al.
Published: (2024)
by: Sun, Kai, et al.
Published: (2024)
CrimeAlarm: Towards Intensive Intent Dynamics in Fine-grained Crime Prediction
by: Hu, Kaixi, et al.
Published: (2024)
by: Hu, Kaixi, et al.
Published: (2024)
OFMU: Optimization-Driven Framework for Machine Unlearning
by: Asif, Sadia, et al.
Published: (2025)
by: Asif, Sadia, et al.
Published: (2025)
Towards Federated Domain Unlearning: Verification Methodologies and Challenges
by: Tam, Kahou, et al.
Published: (2024)
by: Tam, Kahou, et al.
Published: (2024)
Engineering Artificial Intelligence: Framework, Challenges, and Future Direction
by: Lee, Jay, et al.
Published: (2025)
by: Lee, Jay, et al.
Published: (2025)
Federated Learning in Healthcare: Model Misconducts, Security, Challenges, Applications, and Future Research Directions -- A Systematic Review
by: Ali, Md Shahin, et al.
Published: (2024)
by: Ali, Md Shahin, et al.
Published: (2024)
Bridging the Gap Between Preference Alignment and Machine Unlearning
by: Feng, Xiaohua, et al.
Published: (2025)
by: Feng, Xiaohua, et al.
Published: (2025)
Ready2Unlearn: A Learning-Time Approach for Preparing Models with Future Unlearning Readiness
by: Duan, Hanyu, et al.
Published: (2025)
by: Duan, Hanyu, et al.
Published: (2025)
Enhancing Text Generation in Joint NLG/NLU Learning Through Curriculum Learning, Semi-Supervised Training, and Advanced Optimization Techniques
by: Shaik, Rahimanuddin, et al.
Published: (2024)
by: Shaik, Rahimanuddin, et al.
Published: (2024)
Factor Decorrelation Enhanced Data Removal from Deep Predictive Models
by: Yang, Wenhao, et al.
Published: (2025)
by: Yang, Wenhao, et al.
Published: (2025)
Joint Input and Output Coordination for Class-Incremental Learning
by: Wang, Shuai, et al.
Published: (2024)
by: Wang, Shuai, et al.
Published: (2024)
Towards Causal Classification: A Comprehensive Study on Graph Neural Networks
by: Job, Simi, et al.
Published: (2024)
by: Job, Simi, et al.
Published: (2024)
Certified Signed Graph Unlearning
by: Zhao, Junpeng, et al.
Published: (2025)
by: Zhao, Junpeng, et al.
Published: (2025)
A Survey of Cross-domain Graph Learning: Progress and Future Directions
by: Zhao, Haihong, et al.
Published: (2025)
by: Zhao, Haihong, et al.
Published: (2025)
Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning
by: Yang, Puning, et al.
Published: (2025)
by: Yang, Puning, et al.
Published: (2025)
Deep Learning within Tabular Data: Foundations, Challenges, Advances and Future Directions
by: Ren, Weijieying, et al.
Published: (2025)
by: Ren, Weijieying, et al.
Published: (2025)
Randomized Antipodal Search Done Right for Data Pareto Improvement of LLM Unlearning
by: Liu, Ziwen, et al.
Published: (2026)
by: Liu, Ziwen, et al.
Published: (2026)
Probing Knowledge Holes in Unlearned LLMs
by: Ko, Myeongseob, et al.
Published: (2025)
by: Ko, Myeongseob, et al.
Published: (2025)
UniAlign: A Model-Agnostic Framework for Robust Network Traffic Classification under Distribution Shifts
by: Wang, Tongze, et al.
Published: (2026)
by: Wang, Tongze, et al.
Published: (2026)
Controllable Unlearning for Image-to-Image Generative Models via $\varepsilon$-Constrained Optimization
by: Feng, Xiaohua, et al.
Published: (2024)
by: Feng, Xiaohua, et al.
Published: (2024)
DynamicLight: Two-Stage Dynamic Traffic Signal Timing
by: Zhang, Liang, et al.
Published: (2022)
by: Zhang, Liang, et al.
Published: (2022)
Boosting Alignment for Post-Unlearning Text-to-Image Generative Models
by: Ko, Myeongseob, et al.
Published: (2024)
by: Ko, Myeongseob, et al.
Published: (2024)
Similar Items
-
Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and Taxonomy
by: Shaik, Thanveer, et al.
Published: (2023) -
Graph-enabled Reinforcement Learning for Time Series Forecasting with Adaptive Intelligence
by: Shaik, Thanveer, et al.
Published: (2023) -
Adaptive Multi-Agent Deep Reinforcement Learning for Timely Healthcare Interventions
by: Shaik, Thanveer, et al.
Published: (2023) -
FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning
by: Shaik, Thanveer, et al.
Published: (2023) -
Quantum Machine Unlearning: Foundations, Mechanisms, and Taxonomy
by: Shaik, Thanveer, et al.
Published: (2025)