Image de couverture de livre

UMEDA: Unified Multi-modal Efficient Data Fusion for Privacy-Preserving Graph Federated Learning via Spectral-Gated Attention and Diffusion-Based Operator Alignment

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Lai, Shih-Yu, Yamaguchi, Hirozumi, Chen, Shang-Tse, Liu, Yu-Lun, Chen, Bing-Yu
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning Artificial Intelligence Cryptography and Security Distributed, Parallel, and Cluster Computing
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Privacy-Preserving Federated Heavy Hitter Analytics for Non-IID Data
par: Shao, Jiaqi, et autres
Publié: (2023)

ClusterFusion++: Expanding Cluster-Level Fusion to Full Transformer-Block Decoding
par: Jin, ChiHeng, et autres
Publié: (2026)

Experiences Building Enterprise-Level Privacy-Preserving Federated Learning to Power AI for Science
par: Li, Zilinghan, et autres
Publié: (2025)

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks
par: Ambekar, Siddharth, et autres
Publié: (2024)

CacheFL: Privacy-Preserving and Efficient Federated Cache Model Fine-Tuning for Vision-Language Models
par: Yi, Mengjun, et autres
Publié: (2025)

FlashFuser: Expanding the Scale of Kernel Fusion for Compute-Intensive Operators via Inter-Core Connection
par: Huang, Ziyu, et autres
Publié: (2025)

DiffPhD: A Unified Differentiable Solver for Projective Heterogeneous Materials in Elastodynamics with Contact-Rich GPU-Acceleration
par: Lai, Shih-Yu, et autres
Publié: (2026)

Privacy-Preserving and Trustworthy Localization in an IoT Environment
par: Zocca, Guglielmo, et autres
Publié: (2024)

S-HPLB: Efficient LLM Attention Serving via Sparsity-Aware Head Parallelism Load Balance
par: Liu, Di, et autres
Publié: (2026)

DP2Guard: A Lightweight and Byzantine-Robust Privacy-Preserving Federated Learning Scheme for Industrial IoT
par: Han, Baofu, et autres
Publié: (2025)

From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges
par: Li, Qiongxiu, et autres
Publié: (2025)

AB-Sparse: Sparse Attention with Adaptive Block Size for Accurate and Efficient Long-Context Inference
par: Liu, Di, et autres
Publié: (2026)

Prefill-Decode Aggregation or Disaggregation? Unifying Both for Goodput-Optimized LLM Serving
par: Wang, Chao, et autres
Publié: (2025)

AnchorTP: Resilient LLM Inference with State-Preserving Elastic Tensor Parallelism
par: Xu, Wendong, et autres
Publié: (2025)

DFPL: Decentralized Federated Prototype Learning Across Heterogeneous Data Distributions
par: Zhang, Hongliang, et autres
Publié: (2025)

Privacy-Preserving Coding Schemes for Multi-Access Distributed Computing Models
par: Sasi, Shanuja
Publié: (2026)

Privacy-Preserving Sharing of Data Analytics Runtime Metrics for Performance Modeling
par: Will, Jonathan, et autres
Publié: (2024)

DPBalance: Efficient and Fair Privacy Budget Scheduling for Federated Learning as a Service
par: Liu, Yu, et autres
Publié: (2024)

ClusterFusion: Expanding Operator Fusion Scope for LLM Inference via Cluster-Level Collective Primitive
par: Luo, Xinhao, et autres
Publié: (2025)

A Privacy-Preserving Machine Learning Framework for Edge Intelligence: An Empirical Analysis
par: Trieu, Quoc Lap, et autres
Publié: (2026)

Quantum-Inspired Privacy-Preserving Federated Learning Framework for Secure Dementia Classification
par: Tanbhir, Gazi, et autres
Publié: (2025)

FairGFL: Privacy-Preserving Fairness-Aware Federated Learning with Overlapping Subgraphs
par: Zhou, Zihao, et autres
Publié: (2025)

Privacy-Preserving Data Processing in Cloud : From Homomorphic Encryption to Federated Analytics
par: Sarraf, Gaurav, et autres
Publié: (2026)

PPFPL: Cross-silo Privacy-preserving Federated Prototype Learning Against Data Poisoning Attacks
par: Zhang, Hongliang, et autres
Publié: (2025)

RegGuard: Legitimacy and Fairness Enforcement for Optimistic Rollups
par: Shang, Zhenhang, et autres
Publié: (2026)

HHEML: Hybrid Homomorphic Encryption for Privacy-Preserving Machine Learning on Edge
par: Chan, Yu Hin, et autres
Publié: (2025)

Privacy-Preserving and Incentive-Driven Relay-Based Framework for Cross-Domain Blockchain Interoperability
par: Moradi, Saeed, et autres
Publié: (2025)

Janus: Disaggregating Attention and Experts for Scalable MoE Inference
par: Zhang, Zhexiang, et autres
Publié: (2025)

Privacy-Preserving Federated Learning: Integrating Zero-Knowledge Proofs in Scalable Distributed Architectures
par: Gupta, Divya
Publié: (2026)

Advances in Privacy Preserving Federated Learning to Realize a Truly Learning Healthcare System
par: Madduri, Ravi, et autres
Publié: (2024)

Privacy-Preserving Federated Learning with Consistency via Knowledge Distillation Using Conditional Generator
par: Luo, Kangyang, et autres
Publié: (2024)

FUSCO: High-Performance Distributed Data Shuffling via Transformation-Communication Fusion
par: Zhu, Zhuoran, et autres
Publié: (2025)

TACTFL: Temporal Contrastive Training for Multi-modal Federated Learning with Similarity-guided Model Aggregation
par: Sun, Guanxiong, et autres
Publié: (2025)

Privacy-preserving Chunk Scheduling in a BitTorrent Implementation of Federated Learning
par: Li, Naicheng, et autres
Publié: (2026)

Secure and Privacy-Preserving Vertical Federated Learning
par: Jin, Shan, et autres
Publié: (2026)

Dynamic Client Clustering, Bandwidth Allocation, and Workload Optimization for Semi-synchronous Federated Learning
par: Yu, Liangkun, et autres
Publié: (2024)

High Order Collaboration-Oriented Federated Graph Neural Network for Accurate QoS Prediction
par: Chen, Zehuan, et autres
Publié: (2025)

Torpor: GPU-Enabled Serverless Computing for Low-Latency, Resource-Efficient Inference
par: Yu, Minchen, et autres
Publié: (2023)

Lancelot: Towards Efficient and Privacy-Preserving Byzantine-Robust Federated Learning within Fully Homomorphic Encryption
par: Jiang, Siyang, et autres
Publié: (2024)

Accelerating Privacy-Preserving Federated Learning in Large-Scale LEO Satellite Systems
par: Guo, Binquan, et autres
Publié: (2025)