Saved in:
| Main Authors: | Vargis, Tom Richard, Ghiasvand, Siavash |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.05114 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
SProBench: Stream Processing Benchmark for High Performance Computing Infrastructure
by: Kulkarni, Apurv Deepak, et al.
Published: (2025)
by: Kulkarni, Apurv Deepak, et al.
Published: (2025)
Robust Decentralized Learning with Local Updates and Gradient Tracking
by: Ghiasvand, Sajjad, et al.
Published: (2024)
by: Ghiasvand, Sajjad, et al.
Published: (2024)
Seamless Transitions: A Comprehensive Review of Live Migration Technologies
by: Attar-Khorasani, Sima, et al.
Published: (2025)
by: Attar-Khorasani, Sima, et al.
Published: (2025)
FIKIT: Priority-Based Real-time GPU Multi-tasking Scheduling with Kernel Identification
by: Wu, Wenqing
Published: (2023)
by: Wu, Wenqing
Published: (2023)
FedGroup: Efficient Clustered Federated Learning via Decomposed Data-Driven Measure
by: Duan, Moming, et al.
Published: (2020)
by: Duan, Moming, et al.
Published: (2020)
Federated Automated Feature Engineering
by: Overman, Tom, et al.
Published: (2024)
by: Overman, Tom, et al.
Published: (2024)
Convergence Analysis of Split Federated Learning on Heterogeneous Data
by: Han, Pengchao, et al.
Published: (2024)
by: Han, Pengchao, et al.
Published: (2024)
Energy-Efficient Federated Learning for Edge Real-Time Vision via Joint Data, Computation, and Communication Design
by: Hou, Xiangwang, et al.
Published: (2025)
by: Hou, Xiangwang, et al.
Published: (2025)
Towards providing reliable job completion time predictions using PCS
by: Faisal, Abdullah Bin, et al.
Published: (2024)
by: Faisal, Abdullah Bin, et al.
Published: (2024)
Preserving Near-Optimal Gradient Sparsification Cost for Scalable Distributed Deep Learning
by: Yoon, Daegun, et al.
Published: (2024)
by: Yoon, Daegun, et al.
Published: (2024)
Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis
by: Crawshaw, Michael, et al.
Published: (2024)
by: Crawshaw, Michael, et al.
Published: (2024)
Weather Prediction Using CNN-LSTM for Time Series Analysis: A Case Study on Delhi Temperature Data
by: Li, Bangyu, et al.
Published: (2024)
by: Li, Bangyu, et al.
Published: (2024)
Near-Zero-Overhead Freshness for Recommendation Systems via Inference-Side Model Updates
by: Yu, Wenjun, et al.
Published: (2025)
by: Yu, Wenjun, et al.
Published: (2025)
Split Learning-Enabled Framework for Secure and Light-weight Internet of Medical Things Systems
by: Sai, Siva, et al.
Published: (2025)
by: Sai, Siva, et al.
Published: (2025)
FedUHD: Unsupervised Federated Learning using Hyperdimensional Computing
by: Lee, You Hak, et al.
Published: (2025)
by: Lee, You Hak, et al.
Published: (2025)
A Modern Approach to Real-Time Air Traffic Management System
by: Vaidya, Priyank, et al.
Published: (2025)
by: Vaidya, Priyank, et al.
Published: (2025)
Generalization Error Analysis for Attack-Free and Byzantine-Resilient Decentralized Learning with Data Heterogeneity
by: Ye, Haoxiang, et al.
Published: (2025)
by: Ye, Haoxiang, et al.
Published: (2025)
Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications
by: Cremonesi, Francesco, et al.
Published: (2023)
by: Cremonesi, Francesco, et al.
Published: (2023)
MiCRO: Near-Zero Cost Gradient Sparsification for Scaling and Accelerating Distributed DNN Training
by: Yoon, Daegun, et al.
Published: (2023)
by: Yoon, Daegun, et al.
Published: (2023)
Continuous-Time Analysis of Federated Averaging
by: Overman, Tom, et al.
Published: (2025)
by: Overman, Tom, et al.
Published: (2025)
Taming Unbalanced Training Workloads in Deep Learning with Partial Collective Operations
by: Li, Shigang, et al.
Published: (2019)
by: Li, Shigang, et al.
Published: (2019)
What Operations can be Performed Directly on Compressed Arrays, and with What Error?
by: Agarwal, Tripti, et al.
Published: (2024)
by: Agarwal, Tripti, et al.
Published: (2024)
From Models to Operators: Rethinking Autoscaling Granularity for Large Generative Models
by: Cui, Xingqi, et al.
Published: (2025)
by: Cui, Xingqi, et al.
Published: (2025)
Dion2: A Simple Method to Shrink Matrix in Muon
by: Ahn, Kwangjun, et al.
Published: (2025)
by: Ahn, Kwangjun, et al.
Published: (2025)
Near-Optimal Resilient Aggregation Rules for Distributed Learning Using 1-Center and 1-Mean Clustering with Outliers
by: Yi, Yuhao, et al.
Published: (2023)
by: Yi, Yuhao, et al.
Published: (2023)
Context-Driven Performance Modeling for Causal Inference Operators on Neural Processing Units
by: Gupta, Neelesh, et al.
Published: (2025)
by: Gupta, Neelesh, et al.
Published: (2025)
iSpLib: A Library for Accelerating Graph Neural Networks using Auto-tuned Sparse Operations
by: Anik, Md Saidul Hoque, et al.
Published: (2024)
by: Anik, Md Saidul Hoque, et al.
Published: (2024)
TensAIR: Real-Time Training of Neural Networks from Data-streams
by: Tosi, Mauro D. L., et al.
Published: (2022)
by: Tosi, Mauro D. L., et al.
Published: (2022)
A Comprehensive Survey of Federated Transfer Learning: Challenges, Methods and Applications
by: Guo, Wei, et al.
Published: (2024)
by: Guo, Wei, et al.
Published: (2024)
InkStream: Real-time GNN Inference on Streaming Graphs via Incremental Update
by: Wu, Dan, et al.
Published: (2023)
by: Wu, Dan, et al.
Published: (2023)
Floe: Federated Specialization for Real-Time LLM-SLM Inference
by: Tian, Chunlin, et al.
Published: (2026)
by: Tian, Chunlin, et al.
Published: (2026)
A Semantic Partitioning Method for Large-Scale Training of Knowledge Graph Embeddings
by: Bai, Yuhe
Published: (2025)
by: Bai, Yuhe
Published: (2025)
FedDriveScore: Federated Scoring Driving Behavior with a Mixture of Metric Distributions
by: Lu, Lin
Published: (2024)
by: Lu, Lin
Published: (2024)
FLAM: Evaluating Model Performance with Aggregatable Measures in Federated Learning
by: Stricker, Fabian, et al.
Published: (2026)
by: Stricker, Fabian, et al.
Published: (2026)
Nesterov Method for Asynchronous Pipeline Parallel Optimization
by: Ajanthan, Thalaiyasingam, et al.
Published: (2025)
by: Ajanthan, Thalaiyasingam, et al.
Published: (2025)
GPU-Accelerated Optimization of Transformer-Based Neural Networks for Real-Time Inference
by: Mukherjee, Soutrik, et al.
Published: (2026)
by: Mukherjee, Soutrik, et al.
Published: (2026)
MIRA: A Method of Federated MultI-Task Learning for LaRge LAnguage Models
by: Elbakary, Ahmed, et al.
Published: (2024)
by: Elbakary, Ahmed, et al.
Published: (2024)
CLLoRA: An Approach to Measure the Effects of the Context Length for LLM Fine-Tuning
by: Zhang, Ping, et al.
Published: (2025)
by: Zhang, Ping, et al.
Published: (2025)
Unlearning during Learning: An Efficient Federated Machine Unlearning Method
by: Gu, Hanlin, et al.
Published: (2024)
by: Gu, Hanlin, et al.
Published: (2024)
Pipette: Automatic Fine-grained Large Language Model Training Configurator for Real-World Clusters
by: Yim, Jinkyu, et al.
Published: (2024)
by: Yim, Jinkyu, et al.
Published: (2024)
Similar Items
-
SProBench: Stream Processing Benchmark for High Performance Computing Infrastructure
by: Kulkarni, Apurv Deepak, et al.
Published: (2025) -
Robust Decentralized Learning with Local Updates and Gradient Tracking
by: Ghiasvand, Sajjad, et al.
Published: (2024) -
Seamless Transitions: A Comprehensive Review of Live Migration Technologies
by: Attar-Khorasani, Sima, et al.
Published: (2025) -
FIKIT: Priority-Based Real-time GPU Multi-tasking Scheduling with Kernel Identification
by: Wu, Wenqing
Published: (2023) -
FedGroup: Efficient Clustered Federated Learning via Decomposed Data-Driven Measure
by: Duan, Moming, et al.
Published: (2020)