Copertina

Federated Learning for distribution skewed data using sample weights

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Nguyen, Hung, Wu, Peiyuan, Chang, Morris
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Synthetic Information towards Maximum Posterior Ratio for deep learning on Imbalanced Data
di: Nguyen, Hung, et al.
Pubblicazione: (2024)

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

Empowering Contrastive Federated Sequential Recommendation with LLMs
di: Nguyen, Thi Minh Chau, et al.
Pubblicazione: (2026)

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

Training data attribution in diffusion models via mirrored unlearning and noise-consistent skew
di: Serrà, Joan, et al.
Pubblicazione: (2026)

Probabilistic Federated Learning on Uncertain and Heterogeneous Data with Model Personalization
di: Rahman, Ratun, et al.
Pubblicazione: (2026)

Latency-aware Multimodal Federated Learning over UAV Networks
di: Shaon, Shaba, et al.
Pubblicazione: (2025)

A Robust Deep Learning System for Motor Bearing Fault Detection: Leveraging Multiple Learning Strategies and a Novel Double Loss Function
di: Tran, Khoa, et al.
Pubblicazione: (2023)

Hybrid Cross-domain Robust Reinforcement Learning
di: Van, Linh Le Pham, et al.
Pubblicazione: (2025)

CDKT-FL: Cross-Device Knowledge Transfer using Proxy Dataset in Federated Learning
di: Le, Huy Q., et al.
Pubblicazione: (2022)

Decoupled Federated Learning on Long-Tailed and Non-IID data with Feature Statistics
di: Chen, Zhuoxin, et al.
Pubblicazione: (2024)

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

Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization
di: Nguyen, Hy, et al.
Pubblicazione: (2025)

Towards Layer-Wise Personalized Federated Learning: Adaptive Layer Disentanglement via Conflicting Gradients
di: Nguyen, Minh Duong, et al.
Pubblicazione: (2024)

SPaCe: Unlocking Sample-Efficient Large Language Models Training With Self-Pace Curriculum Learning
di: Do, Dai, et al.
Pubblicazione: (2025)

SA-EMO: Structure-Aligned Encoder Mixture of Operators for Generalizable Full-waveform Inversion
di: Zhenyu, Wang, et al.
Pubblicazione: (2025)

From Federated Learning to Quantum Federated Learning for Space-Air-Ground Integrated Networks
di: Quy, Vu Khanh, et al.
Pubblicazione: (2024)

Exploiting Meta-Learning-based Poisoning Attacks for Graph Link Prediction
di: Li, Mingchen, et al.
Pubblicazione: (2025)

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

DmC: Nearest Neighbor Guidance Diffusion Model for Offline Cross-domain Reinforcement Learning
di: Van, Linh Le Pham, et al.
Pubblicazione: (2025)

FLoRA: Enhancing Vision-Language Models with Parameter-Efficient Federated Learning
di: Nguyen, Duy Phuong, et al.
Pubblicazione: (2024)

Predicting Survival of Hemodialysis Patients using Federated Learning
di: Raju, Abhiram, et al.
Pubblicazione: (2024)

Personalized Federated Learning via Learning Dynamic Graphs
di: Zhou, Ziran, et al.
Pubblicazione: (2025)

Federated Learning with Differential Privacy: An Utility-Enhanced Approach
di: Ranaweera, Kanishka, et al.
Pubblicazione: (2025)

CHoE: Cross-Domain Heterogeneous Graph Prompt Learning via Structure-Conditioned Experts
di: Li, Peiyuan, et al.
Pubblicazione: (2026)

Regret-Guided Search Control for Efficient Learning in AlphaZero
di: Tsai, Yun-Jui, et al.
Pubblicazione: (2026)

Graph Federated Learning for Personalized Privacy Recommendation
di: Na, Ce, et al.
Pubblicazione: (2025)

Energy-Efficient Federated Learning for AIoT using Clustering Methods
di: Pereira, Roberto, et al.
Pubblicazione: (2025)

Principled Data Augmentation for Learning to Solve Quadratic Programming Problems
di: Qian, Chendi, et al.
Pubblicazione: (2025)

Mitigating Time Discretization Challenges with WeatherODE: A Sandwich Physics-Driven Neural ODE for Weather Forecasting
di: Liu, Peiyuan, et al.
Pubblicazione: (2024)

IndexNet: Timestamp and Variable-Aware Modeling for Time Series Forecasting
di: Wu, Beiliang, et al.
Pubblicazione: (2025)

Variational Flow Models: Flowing in Your Style
di: Do, Kien, et al.
Pubblicazione: (2024)

d3LLM: Ultra-Fast Diffusion LLM using Pseudo-Trajectory Distillation
di: Qian, Yu-Yang, et al.
Pubblicazione: (2026)

Resource-efficient Layer-wise Federated Self-supervised Learning
di: Tun, Ye Lin, et al.
Pubblicazione: (2024)

Mitigating Participation Imbalance Bias in Asynchronous Federated Learning
di: Chang, Xiangyu, et al.
Pubblicazione: (2025)

Privacy-Preserved Automated Scoring using Federated Learning for Educational Research
di: Latif, Ehsan, et al.
Pubblicazione: (2025)

SeqBattNet: A Discrete-State Physics-Informed Neural Network with Aging Adaptation for Battery Modeling
di: Tran, Khoa, et al.
Pubblicazione: (2025)

Federated Learning with Sample-level Client Drift Mitigation
di: Xu, Haoran, et al.
Pubblicazione: (2025)

FDRMFL:Multi-modal Federated Feature Extraction Model Based on Information Maximization and Contrastive Learning
di: Wu, Haozhe
Pubblicazione: (2025)

Remote Rowhammer Attack using Adversarial Observations on Federated Learning Clients
di: Yuan, Jinsheng, et al.
Pubblicazione: (2025)