Saved in:
| Main Authors: | Wang, Ming, Duan, Zhaoyang, Xue, Dong, Liu, Fangzhou, Zhang, Zhongheng |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.08050 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Doctor Sun: A Bilingual Multimodal Large Language Model for Biomedical AI
by: Xue, Dong, et al.
Published: (2025)
by: Xue, Dong, et al.
Published: (2025)
Dynamic User-controllable Privacy-preserving Few-shot Sensing Framework
by: Chathoth, Ajesh Koyatan, et al.
Published: (2025)
by: Chathoth, Ajesh Koyatan, et al.
Published: (2025)
GCFL: A Gradient Correction-based Federated Learning Framework for Privacy-preserving CPSS
by: Wan, Jiayi, et al.
Published: (2025)
by: Wan, Jiayi, et al.
Published: (2025)
A Game-theoretic Framework for Privacy-preserving Federated Learning
by: Zhang, Xiaojin, et al.
Published: (2023)
by: Zhang, Xiaojin, et al.
Published: (2023)
Federated Learning with Differential Privacy: An Utility-Enhanced Approach
by: Ranaweera, Kanishka, et al.
Published: (2025)
by: Ranaweera, Kanishka, et al.
Published: (2025)
Data Valuation for Vertical Federated Learning: A Model-free and Privacy-preserving Method
by: Han, Xiao, et al.
Published: (2021)
by: Han, Xiao, et al.
Published: (2021)
Few-shot Class-incremental Fault Diagnosis by Preserving Class-Agnostic Knowledge with Dual-Granularity Representations
by: Yang, Zhendong, et al.
Published: (2025)
by: Yang, Zhendong, et al.
Published: (2025)
Episodic-free Task Selection for Few-shot Learning
by: Zhang, Tao
Published: (2024)
by: Zhang, Tao
Published: (2024)
Collaborative Cognitive Diagnosis with Disentangled Representation Learning for Learner Modeling
by: Gao, Weibo, et al.
Published: (2024)
by: Gao, Weibo, et al.
Published: (2024)
Adaptive Clipping for Privacy-Preserving Few-Shot Learning: Enhancing Generalization with Limited Data
by: Ranaweera, Kanishka, et al.
Published: (2025)
by: Ranaweera, Kanishka, et al.
Published: (2025)
Tri-MTL: A Triple Multitask Learning Approach for Respiratory Disease Diagnosis
by: Kim, June-Woo, et al.
Published: (2025)
by: Kim, June-Woo, et al.
Published: (2025)
Federated Few-Shot Learning for Epileptic Seizure Detection Under Privacy Constraints
by: Sysoykova, Ekaterina, et al.
Published: (2025)
by: Sysoykova, Ekaterina, et al.
Published: (2025)
Engineering FAIR Privacy-preserving Applications that Learn Histories of Disease
by: Duarte, Ines N., et al.
Published: (2026)
by: Duarte, Ines N., et al.
Published: (2026)
Frequency Enhanced Pre-training for Cross-city Few-shot Traffic Forecasting
by: Liu, Zhanyu, et al.
Published: (2024)
by: Liu, Zhanyu, et al.
Published: (2024)
Few-shot Class-incremental Learning for Classification and Object Detection: A Survey
by: Zhang, Jinghua, et al.
Published: (2023)
by: Zhang, Jinghua, et al.
Published: (2023)
FewFedPIT: Towards Privacy-preserving and Few-shot Federated Instruction Tuning
by: Zhang, Zhuo, et al.
Published: (2024)
by: Zhang, Zhuo, et al.
Published: (2024)
Few-for-Many Personalized Federated Learning
by: Guo, Ping, et al.
Published: (2026)
by: Guo, Ping, et al.
Published: (2026)
ICPL: Few-shot In-context Preference Learning via LLMs
by: Yu, Chao, et al.
Published: (2024)
by: Yu, Chao, et al.
Published: (2024)
Enhancing Model Privacy in Federated Learning with Random Masking and Quantization
by: Xu, Zhibo, et al.
Published: (2025)
by: Xu, Zhibo, et al.
Published: (2025)
Towards Few-shot Self-explaining Graph Neural Networks
by: Peng, Jingyu, et al.
Published: (2024)
by: Peng, Jingyu, et al.
Published: (2024)
Neural Force Field: Few-shot Learning of Generalized Physical Reasoning
by: Li, Shiqian, et al.
Published: (2025)
by: Li, Shiqian, et al.
Published: (2025)
Improving Graph Few-shot Learning with Hyperbolic Space and Denoising Diffusion
by: Liu, Yonghao, et al.
Published: (2026)
by: Liu, Yonghao, et al.
Published: (2026)
Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning
by: Xu, Qi, et al.
Published: (2025)
by: Xu, Qi, et al.
Published: (2025)
A Federated Learning Framework for Handling Subtype Confounding and Heterogeneity in Large-Scale Neuroimaging Diagnosis
by: Zhao, Xinglin, et al.
Published: (2025)
by: Zhao, Xinglin, et al.
Published: (2025)
Revisiting Chain-of-Thought Prompting: Zero-shot Can Be Stronger than Few-shot
by: Cheng, Xiang, et al.
Published: (2025)
by: Cheng, Xiang, et al.
Published: (2025)
One-shot Federated Learning Methods: A Practical Guide
by: Liu, Xiang, et al.
Published: (2025)
by: Liu, Xiang, et al.
Published: (2025)
TransNet: Transfer Knowledge for Few-shot Knowledge Graph Completion
by: Liu, Lihui, et al.
Published: (2025)
by: Liu, Lihui, et al.
Published: (2025)
Explainable Machine Learning Framework for Cardiovascular Disease Diagnosis and Prognosis
by: Sourov, Md. Emon Akter, et al.
Published: (2025)
by: Sourov, Md. Emon Akter, et al.
Published: (2025)
Proto-EVFL: Enhanced Vertical Federated Learning via Dual Prototype with Extremely Unaligned Data
by: Guo, Wei, et al.
Published: (2025)
by: Guo, Wei, et al.
Published: (2025)
DP$^2$-NILM: A Distributed and Privacy-preserving Framework for Non-intrusive Load Monitoring
by: Dai, Shuang, et al.
Published: (2022)
by: Dai, Shuang, et al.
Published: (2022)
Provable Sparse Inversion and Token Relabel Enhanced One-shot Federated Learning with ViTs
by: Shen, Li, et al.
Published: (2026)
by: Shen, Li, et al.
Published: (2026)
Graph Federated Learning for Personalized Privacy Recommendation
by: Na, Ce, et al.
Published: (2025)
by: Na, Ce, et al.
Published: (2025)
FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation
by: Liu, Xiang, et al.
Published: (2023)
by: Liu, Xiang, et al.
Published: (2023)
Synthetic Forgetting without Access: A Few-shot Zero-glance Framework for Machine Unlearning
by: Song, Qipeng, et al.
Published: (2025)
by: Song, Qipeng, et al.
Published: (2025)
Differential Privacy-Driven Framework for Enhancing Heart Disease Prediction
by: Otoum, Yazan, et al.
Published: (2025)
by: Otoum, Yazan, et al.
Published: (2025)
Multi-Objective Optimization for Privacy-Utility Balance in Differentially Private Federated Learning
by: Ranaweera, Kanishka, et al.
Published: (2025)
by: Ranaweera, Kanishka, et al.
Published: (2025)
SDFLoRA: Selective Decoupled Federated LoRA for Privacy-preserving Fine-tuning with Heterogeneous Clients
by: Shen, Zhikang, et al.
Published: (2026)
by: Shen, Zhikang, et al.
Published: (2026)
Parametric Feature Transfer: One-shot Federated Learning with Foundation Models
by: Beitollahi, Mahdi, et al.
Published: (2024)
by: Beitollahi, Mahdi, et al.
Published: (2024)
Opening the Black Box: An Explainable, Few-shot AI4E Framework Informed by Physics and Expert Knowledge for Materials Engineering
by: Zhang, Haoxiang, et al.
Published: (2025)
by: Zhang, Haoxiang, et al.
Published: (2025)
Cooperative Open-ended Learning Framework for Zero-shot Coordination
by: Li, Yang, et al.
Published: (2023)
by: Li, Yang, et al.
Published: (2023)
Similar Items
-
Doctor Sun: A Bilingual Multimodal Large Language Model for Biomedical AI
by: Xue, Dong, et al.
Published: (2025) -
Dynamic User-controllable Privacy-preserving Few-shot Sensing Framework
by: Chathoth, Ajesh Koyatan, et al.
Published: (2025) -
GCFL: A Gradient Correction-based Federated Learning Framework for Privacy-preserving CPSS
by: Wan, Jiayi, et al.
Published: (2025) -
A Game-theoretic Framework for Privacy-preserving Federated Learning
by: Zhang, Xiaojin, et al.
Published: (2023) -
Federated Learning with Differential Privacy: An Utility-Enhanced Approach
by: Ranaweera, Kanishka, et al.
Published: (2025)