Saved in:
| Main Author: | Krishna, Gutha Jaya |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2404.03665 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
TPI-LLM: Serving 70B-scale LLMs Efficiently on Low-resource Edge Devices
by: Li, Zonghang, et al.
Published: (2024)
by: Li, Zonghang, et al.
Published: (2024)
Prima.cpp: Fast 30-70B LLM Inference on Heterogeneous and Low-Resource Home Clusters
by: Li, Zonghang, et al.
Published: (2025)
by: Li, Zonghang, et al.
Published: (2025)
EPARA: Parallelizing Categorized AI Inference in Edge Clouds
by: Wang, Yubo, et al.
Published: (2025)
by: Wang, Yubo, et al.
Published: (2025)
Learning In Chaos: Efficient Autoscaling and Self-Healing for Multi-Party Distributed Training
by: Feng, Wenjiao, et al.
Published: (2025)
by: Feng, Wenjiao, et al.
Published: (2025)
SI-ChainFL: Shapley-Incentivized Secure Federated Learning for High-Speed Rail Data Sharing
by: Zhao, Mingjie, et al.
Published: (2026)
by: Zhao, Mingjie, et al.
Published: (2026)
Massively Parallel Genetic Optimization through Asynchronous Propagation of Populations
by: Taubert, Oskar, et al.
Published: (2023)
by: Taubert, Oskar, et al.
Published: (2023)
Connecting Large Language Model Agent to High Performance Computing Resource
by: Ma, Heng, et al.
Published: (2025)
by: Ma, Heng, et al.
Published: (2025)
How Machine Learning-Data Driven Replication Strategies Enhance Fault Tolerance in Large-Scale Distributed Systems
by: Murimi, Almond Kiruthu
Published: (2025)
by: Murimi, Almond Kiruthu
Published: (2025)
Data Scheduling Algorithm for Scalable and Efficient IoT Sensing in Cloud Computing
by: Mohammad, Noor Islam S.
Published: (2025)
by: Mohammad, Noor Islam S.
Published: (2025)
SPARK: Igniting Communication-Efficient Decentralized Learning via Stage-wise Projected NTK and Accelerated Regularization
by: Xia, Li
Published: (2025)
by: Xia, Li
Published: (2025)
SmartEdge: Smart Healthcare End-to-End Integrated Edge and Cloud Computing System for Diabetes Prediction Enabled by Ensemble Machine Learning
by: Hennebelle, Alain, et al.
Published: (2025)
by: Hennebelle, Alain, et al.
Published: (2025)
Roadmap for Edge AI: A Dagstuhl Perspective
by: Ding, Aaron Yi, et al.
Published: (2021)
by: Ding, Aaron Yi, et al.
Published: (2021)
Accelerating Geo-distributed Machine Learning with Network-Aware Adaptive Tree and Auxiliary Route
by: Li, Zonghang, et al.
Published: (2024)
by: Li, Zonghang, et al.
Published: (2024)
WLB-LLM: Workload-Balanced 4D Parallelism for Large Language Model Training
by: Wang, Zheng, et al.
Published: (2025)
by: Wang, Zheng, et al.
Published: (2025)
Federated Learning for Anomaly Detection in Energy Consumption Data: Assessing the Vulnerability to Adversarial Attacks
by: Telila, Yohannis Kifle, et al.
Published: (2025)
by: Telila, Yohannis Kifle, et al.
Published: (2025)
CodeCRDT: Observation-Driven Coordination for Multi-Agent LLM Code Generation
by: Pugachev, Sergey
Published: (2025)
by: Pugachev, Sergey
Published: (2025)
Separating Intelligence from Execution: A Workflow Engine for the Model Context Protocol
by: Parmar, Abhinav Singh
Published: (2026)
by: Parmar, Abhinav Singh
Published: (2026)
Comparison of Autoscaling Frameworks for Containerised Machine-Learning-Applications in a Local and Cloud Environment
by: Schroeder, Christian, et al.
Published: (2023)
by: Schroeder, Christian, et al.
Published: (2023)
FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores
by: Shi, Jinliang, et al.
Published: (2024)
by: Shi, Jinliang, et al.
Published: (2024)
Hyper-parameter Optimization for Federated Learning with Step-wise Adaptive Mechanism
by: Saadati, Yasaman, et al.
Published: (2024)
by: Saadati, Yasaman, et al.
Published: (2024)
Combinatorial Client-Master Multiagent Deep Reinforcement Learning for Task Offloading in Mobile Edge Computing
by: Gebrekidan, Tesfay Zemuy, et al.
Published: (2024)
by: Gebrekidan, Tesfay Zemuy, et al.
Published: (2024)
Uncertainty Estimation in Multi-Agent Distributed Learning for AI-Enabled Edge Devices
by: Radchenko, Gleb, et al.
Published: (2024)
by: Radchenko, Gleb, et al.
Published: (2024)
Federated Learning with Differential Privacy
by: Banse, Adrien, et al.
Published: (2024)
by: Banse, Adrien, et al.
Published: (2024)
A collaborative ensemble construction method for federated random forest
by: Lim, Penjan Antonio Eng, et al.
Published: (2024)
by: Lim, Penjan Antonio Eng, et al.
Published: (2024)
Partitioned Neural Network Training via Synthetic Intermediate Labels
by: Karadağ, Cevat Volkan, et al.
Published: (2024)
by: Karadağ, Cevat Volkan, et al.
Published: (2024)
Aergia: Leveraging Heterogeneity in Federated Learning Systems
by: Cox, Bart, et al.
Published: (2022)
by: Cox, Bart, et al.
Published: (2022)
Towards Optimal Heterogeneous Client Sampling in Multi-Model Federated Learning
by: Zhang, Haoran, et al.
Published: (2025)
by: Zhang, Haoran, et al.
Published: (2025)
Parameterizing Federated Continual Learning for Reproducible Research
by: Cox, Bart, et al.
Published: (2024)
by: Cox, Bart, et al.
Published: (2024)
Asynchronous Byzantine Federated Learning
by: Cox, Bart, et al.
Published: (2024)
by: Cox, Bart, et al.
Published: (2024)
Training Diffusion Models with Federated Learning
by: de Goede, Matthijs, et al.
Published: (2024)
by: de Goede, Matthijs, et al.
Published: (2024)
Quantize Once, Train Fast: Allreduce-Compatible Compression with Provable Guarantees
by: Xin, Jihao, et al.
Published: (2023)
by: Xin, Jihao, et al.
Published: (2023)
Asynchronous Multi-Server Federated Learning for Geo-Distributed Clients
by: Zuo, Yuncong, et al.
Published: (2024)
by: Zuo, Yuncong, et al.
Published: (2024)
Towards Building Private LLMs: Exploring Multi-Node Expert Parallelism on Apple Silicon for Mixture-of-Experts Large Language Model
by: Chen, Mu-Chi, et al.
Published: (2025)
by: Chen, Mu-Chi, et al.
Published: (2025)
Adaptive GPU Resource Allocation for Multi-Agent Collaborative Reasoning in Serverless Environments
by: Zhang, Guilin, et al.
Published: (2025)
by: Zhang, Guilin, et al.
Published: (2025)
AMP4EC: Adaptive Model Partitioning Framework for Efficient Deep Learning Inference in Edge Computing Environments
by: Zhang, Guilin, et al.
Published: (2025)
by: Zhang, Guilin, et al.
Published: (2025)
A Survey on Efficient Federated Learning Methods for Foundation Model Training
by: Woisetschläger, Herbert, et al.
Published: (2024)
by: Woisetschläger, Herbert, et al.
Published: (2024)
Securing Federated Sensitive Topic Classification against Poisoning Attacks
by: Chu, Tianyue, et al.
Published: (2022)
by: Chu, Tianyue, et al.
Published: (2022)
Bridging Generalization Gap of Heterogeneous Federated Clients Using Generative Models
by: Niu, Ziru, et al.
Published: (2025)
by: Niu, Ziru, et al.
Published: (2025)
LayerKV: Optimizing Large Language Model Serving with Layer-wise KV Cache Management
by: Xiong, Yi, et al.
Published: (2024)
by: Xiong, Yi, et al.
Published: (2024)
Federated Domain Generalization with Data-free On-server Matching Gradient
by: Nguyen, Trong-Binh, et al.
Published: (2025)
by: Nguyen, Trong-Binh, et al.
Published: (2025)
Similar Items
-
TPI-LLM: Serving 70B-scale LLMs Efficiently on Low-resource Edge Devices
by: Li, Zonghang, et al.
Published: (2024) -
Prima.cpp: Fast 30-70B LLM Inference on Heterogeneous and Low-Resource Home Clusters
by: Li, Zonghang, et al.
Published: (2025) -
EPARA: Parallelizing Categorized AI Inference in Edge Clouds
by: Wang, Yubo, et al.
Published: (2025) -
Learning In Chaos: Efficient Autoscaling and Self-Healing for Multi-Party Distributed Training
by: Feng, Wenjiao, et al.
Published: (2025) -
SI-ChainFL: Shapley-Incentivized Secure Federated Learning for High-Speed Rail Data Sharing
by: Zhao, Mingjie, et al.
Published: (2026)