Copertina

Rethinking Knowledge Distillation in Collaborative Machine Learning: Memory, Knowledge, and Their Interactions

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Han, Pengchao, Huang, Xi, Fang, Yi, Han, Guojun
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Distributed, Parallel, and Cluster Computing
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

FedAL: Black-Box Federated Knowledge Distillation Enabled by Adversarial Learning
di: Han, Pengchao, et al.
Pubblicazione: (2023)

Convergence Analysis of Split Federated Learning on Heterogeneous Data
di: Han, Pengchao, et al.
Pubblicazione: (2024)

A Knowledge Distillation-empowered Adaptive Federated Reinforcement Learning Framework for Multi-Domain IoT Applications Scheduling
di: Wang, Zhiyu, et al.
Pubblicazione: (2025)

Efficient CPU-GPU Collaborative Inference for MoE-based LLMs on Memory-Limited Systems
di: Huang, En-Ming, et al.
Pubblicazione: (2025)

LOCO: Rethinking Objects for Network Memory
di: Hodgkins, George, et al.
Pubblicazione: (2025)

Flexible Personalized Split Federated Learning for On-Device Fine-Tuning of Foundation Models
di: Yuan, Tianjun, et al.
Pubblicazione: (2025)

UniTrans: A Unified Vertical Federated Knowledge Transfer Framework for Enhancing Cross-Hospital Collaboration
di: Huang, Chung-ju, et al.
Pubblicazione: (2025)

Flash-KMeans: Fast and Memory-Efficient Exact K-Means
di: Yang, Shuo, et al.
Pubblicazione: (2026)

Propius: A Platform for Collaborative Machine Learning across the Edge and the Cloud
di: Ding, Eric
Pubblicazione: (2025)

Collaborative Multi-Agent Reinforcement Learning Approach for Elastic Cloud Resource Scaling
di: Fang, Bruce, et al.
Pubblicazione: (2025)

UNIDEAL: Curriculum Knowledge Distillation Federated Learning
di: Yang, Yuwen, et al.
Pubblicazione: (2023)

EACO-RAG: Towards Distributed Tiered LLM Deployment using Edge-Assisted and Collaborative RAG with Adaptive Knowledge Update
di: Li, Jiaxing, et al.
Pubblicazione: (2024)

Model Checking and Synthesis for Optimal Use of Knowledge in Consensus Protocols
di: Alpturer, Kaya, et al.
Pubblicazione: (2025)

Homogenizing Non-IID datasets via In-Distribution Knowledge Distillation for Decentralized Learning
di: Ravikumar, Deepak, et al.
Pubblicazione: (2023)

MemAscend: System Memory Optimization for SSD-Offloaded LLM Fine-Tuning
di: Liaw, Yong-Cheng, et al.
Pubblicazione: (2025)

Analysis and Optimized CXL-Attached Memory Allocation for Long-Context LLM Fine-Tuning
di: Liaw, Yong-Cheng, et al.
Pubblicazione: (2025)

SemiDFL: A Semi-Supervised Paradigm for Decentralized Federated Learning
di: Liu, Xinyang, et al.
Pubblicazione: (2024)

Privacy-Preserving Federated Learning with Consistency via Knowledge Distillation Using Conditional Generator
di: Luo, Kangyang, et al.
Pubblicazione: (2024)

Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions
di: Qin, Laiqiao, et al.
Pubblicazione: (2024)

Collaborative Evolution of Intelligent Agents in Large-Scale Microservice Systems
di: Li, Yilin, et al.
Pubblicazione: (2025)

WindVE: Collaborative CPU-NPU Vector Embedding
di: Huang, Jinqi, et al.
Pubblicazione: (2025)

AgentFlow: Resilient Adaptive Cloud-Edge Framework for Multi-Agent Coordination
di: Chen, Ching Han, et al.
Pubblicazione: (2025)

LIME:Accelerating Collaborative Lossless LLM Inference on Memory-Constrained Edge Devices
di: Sun, Mingyu, et al.
Pubblicazione: (2025)

A Knowledge-Based Analysis of Intersection Protocols
di: Alpturer, Kaya, et al.
Pubblicazione: (2024)

FedCache: A Knowledge Cache-driven Federated Learning Architecture for Personalized Edge Intelligence
di: Wu, Zhiyuan, et al.
Pubblicazione: (2023)

Clustered Federated Learning with Hierarchical Knowledge Distillation
di: Ahmad, Sabtain, et al.
Pubblicazione: (2025)

Distributed Non-Interactive Zero-Knowledge Proofs
di: Grilo, Alex B., et al.
Pubblicazione: (2025)

KCES: A Workflow Containerization Scheduling Scheme Under Cloud-Edge Collaboration Framework
di: Shan, Chenggang, et al.
Pubblicazione: (2024)

Distributed Statistical Zero-Knowledge Proofs via Sumcheck
di: Jauregui, Benjamin, et al.
Pubblicazione: (2026)

Orchestrating Federated Learning in Space-Air-Ground Integrated Networks: Adaptive Data Offloading and Seamless Handover
di: Han, Dong-Jun, et al.
Pubblicazione: (2024)

Parallel Collaborative ADMM Privacy Computing and Adaptive GPU Acceleration for Distributed Edge Networks
di: Xia, Mengchun, et al.
Pubblicazione: (2026)

FedRIR: Rethinking Information Representation in Federated Learning
di: Huang, Yongqiang, et al.
Pubblicazione: (2025)

PipeSD: An Efficient Cloud-Edge Collaborative Pipeline Inference Framework with Speculative Decoding
di: Han, Yunhe, et al.
Pubblicazione: (2026)

Collaborative State Machines: A Better Programming Model for the Cloud-Edge-IoT Continuum
di: Etheredge, Marlon, et al.
Pubblicazione: (2025)

Knowledge-driven Reasoning for Mobile Agentic AI: Concepts, Approaches, and Directions
di: Liu, Guangyuan, et al.
Pubblicazione: (2026)

Leveraging Structural Knowledge for Solving Election in Anonymous Networks with Shared Randomness
di: Chalopin, Jérémie, et al.
Pubblicazione: (2026)

Back to the Future: Rethinking Endorsement in Order-Execute Blockchains
di: Huang, Rongji, et al.
Pubblicazione: (2026)

Sentinel: Dynamic Knowledge Distillation for Personalized Federated Intrusion Detection in Heterogeneous IoT Networks
di: Singh, Gurpreet, et al.
Pubblicazione: (2025)

ECCENTRIC: Edge-Cloud Collaboration Framework for Distributed Inference Using Knowledge Adaptation
di: Kamani, Mohammad Mahdi, et al.
Pubblicazione: (2025)

Elastic Mixture of Rank-Wise Experts for Knowledge Reuse in Federated Fine-Tuning
di: Wu, Yebo, et al.
Pubblicazione: (2025)