Imagen de Portada

Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Weng, Pei-Yau, Hoang, Minh, Nguyen, Lam M., Thai, My T., Weng, Tsui-Wei, Hoang, Trong Nghia
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Leveraging Soft Prompts for Privacy Attacks in Federated Prompt Tuning
por: Nguyen, Quan Minh, et al.
Publicado: (2026)

Rethinking Cross-Modal Fine-Tuning: Optimizing the Interaction Between Feature Alignment and Target Fitting
por: Tran, Trong Khiem, et al.
Publicado: (2026)

Learning Surrogates for Offline Black-Box Optimization via Gradient Matching
por: Hoang, Minh, et al.
Publicado: (2025)

Learning Reconfigurable Representations for Multimodal Federated Learning with Missing Data
por: Nguyen, Duong M., et al.
Publicado: (2025)

Revisiting Kernel Attention with Correlated Gaussian Process Representation
por: Bui, Long Minh, et al.
Publicado: (2025)

Black-Box Optimization From Small Offline Datasets via Meta Learning with Synthetic Tasks
por: Fadhel, Azza, et al.
Publicado: (2026)

Causal Graph Learning via Distributional Invariance of Cause-Effect Relationship
por: Nguyen, Nang Hung, et al.
Publicado: (2026)

Federated Active Learning Under Extreme Non-IID and Global Class Imbalance
por: Zong, Chen-Chen, et al.
Publicado: (2026)

Offline Model-Based Optimization via Policy-Guided Gradient Search
por: Chemingui, Yassine, et al.
Publicado: (2024)

RAT: Boosting Misclassification Detection Ability without Extra Data
por: Yan, Ge, et al.
Publicado: (2025)

CHARME: A chain-based reinforcement learning approach for the minor embedding problem
por: Ngo, Hoang M., et al.
Publicado: (2024)

Continual Fine-Tuning with Provably Accurate and Parameter-Free Task Retrieval
por: Le, Hang Thi-Thuy, et al.
Publicado: (2026)

Federated Self-Supervised Learning for Automatic Modulation Classification under Non-IID and Class-Imbalanced Data
por: Akram, Usman, et al.
Publicado: (2025)

Dataset Distillation-based Hybrid Federated Learning on Non-IID Data
por: Shi, Xiufang, et al.
Publicado: (2024)

Faithful and Stable Neuron Explanations for Trustworthy Mechanistic Interpretability
por: Yan, Ge, et al.
Publicado: (2025)

Federated Prompt-Tuning with Heterogeneous and Incomplete Multimodal Client Data
por: Phung, Thu Hang, et al.
Publicado: (2026)

Rethinking the Representation in Federated Unsupervised Learning with Non-IID Data
por: Liao, Xinting, et al.
Publicado: (2024)

Evaluating Federated Kolmogorov-Arnold Networks on Non-IID Data
por: Sasse, Arthur Mendonça, et al.
Publicado: (2024)

Federated Loss Exploration for Improved Convergence on Non-IID Data
por: Internò, Christian, et al.
Publicado: (2025)

Understanding Federated Learning from IID to Non-IID dataset: An Experimental Study
por: Seo, Jungwon, et al.
Publicado: (2025)

Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents
por: Sun, Chung-En, et al.
Publicado: (2024)

A Thorough Assessment of the Non-IID Data Impact in Federated Learning
por: Jimenez-Gutierrez, Daniel M., et al.
Publicado: (2025)

BRIDGE: Bundle Recommendation via Instruction-Driven Generation
por: Bui, Tuan-Nghia, et al.
Publicado: (2024)

Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity
por: Ran, Yide, et al.
Publicado: (2025)

Learning Critically: Selective Self Distillation in Federated Learning on Non-IID Data
por: He, Yuting, et al.
Publicado: (2025)

Variable-Agnostic Causal Exploration for Reinforcement Learning
por: Nguyen, Minh Hoang, et al.
Publicado: (2024)

Semantic Optimal Transport for Sparse Autoencoder Feature Matching and Circuit Compression
por: Cao, Tue M., et al.
Publicado: (2026)

Multiple-Input Variational Auto-Encoder for Anomaly Detection in Heterogeneous Data
por: Dinh, Phai Vu, et al.
Publicado: (2025)

A Robust Clustered Federated Learning Approach for Non-IID Data with Quantity Skew
por: Ali, Michael Ben, et al.
Publicado: (2025)

MultiConfederated Learning: Inclusive Non-IID Data handling with Decentralized Federated Learning
por: Duchesne, Michael, et al.
Publicado: (2024)

AFCL: Analytic Federated Continual Learning for Spatio-Temporal Invariance of Non-IID Data
por: Tang, Jianheng, et al.
Publicado: (2025)

TriplePlay: Enhancing Federated Learning with CLIP for Non-IID Data and Resource Efficiency
por: Imteaj, Ahmed, et al.
Publicado: (2024)

Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecasting
por: Nguyen, Huu Hiep, et al.
Publicado: (2026)

Point Cloud Compression with Bits-back Coding
por: Hieu, Nguyen Quang, et al.
Publicado: (2024)

OvA-LP: A Simple and Efficient Framework for Federated Learning on Non-IID Data
por: Park, Dongjin, et al.
Publicado: (2025)

Energy-Efficient and Real-Time Sensing for Federated Continual Learning via Sample-Driven Control
por: Luu, Minh Ngoc, et al.
Publicado: (2023)

Provably Robust Conformal Prediction with Improved Efficiency
por: Yan, Ge, et al.
Publicado: (2024)

Tackling the Non-IID Issue in Heterogeneous Federated Learning by Gradient Harmonization
por: Zhang, Xinyu, et al.
Publicado: (2023)

Taming Preconditioner Drift: Unlocking the Potential of Second-Order Optimizers for Federated Learning on Non-IID Data
por: Liu, Junkang, et al.
Publicado: (2026)

Understanding Fixed Predictions via Confined Regions
por: Lawless, Connor, et al.
Publicado: (2025)