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Distributed Computing

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Showing 176–200 of 379 papers

TitleStatusHype
Short-Dot: Computing Large Linear Transforms Distributedly Using Coded Short Dot Products—0
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities—0
Simplicial Models for the Epistemic Logic of Faulty Agents—0
Simplification of Graph Convolutional Networks: A Matrix Factorization-based Perspective—0
SlimFL: Federated Learning with Superposition Coding over Slimmable Neural Networks—0
SnapMode: An Intelligent and Distributed Large-Scale Fashion Image Retrieval Platform Based On Big Data and Deep Generative Adversarial Network Technologies—0
Solving Billion-Scale Knapsack Problems—0
Sparse L^1-Autoencoders for Scientific Data Compression—0
Splash: User-friendly Programming Interface for Parallelizing Stochastic Algorithms—0
SplitNets: Designing Neural Architectures for Efficient Distributed Computing on Head-Mounted Systems—0
Stability of Primal-Dual Gradient Flow Dynamics for Multi-Block Convex Optimization Problems—0
Staleness-Alleviated Distributed GNN Training via Online Dynamic-Embedding Prediction—0
Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization—0
STORM: Foundations of End-to-End Empirical Risk Minimization on the Edge—0
Streaming IoT Data and the Quantum Edge: A Classic/Quantum Machine Learning Use Case—0
Structural biology in the clouds: The WeNMR-EOSC Ecosystem—0
Structure-Aware Dynamic Scheduler for Parallel Machine Learning—0
Supporting the development of Machine Learning for fundamental science in a federated Cloud with the AI_INFN platform—0
Surrogate-assisted distributed swarm optimisation for computationally expensive geoscientific models—0
Tag-Weighted Topic Model For Large-scale Semi-Structured Documents—0
Taming Momentum in a Distributed Asynchronous Environment—0
The Giving Game—0
The intelligent prediction and assessment of financial information risk in the cloud computing model—0
The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning—0
Toward Creating Subsurface Camera—0
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