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Distributed Computing

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Showing 276–300 of 379 papers

TitleStatusHype
Quasi-Newton Methods for Machine Learning: Forget the Past, Just SampleCode0
Distributed Learning with Compressed Gradient Differences—0
DINGO: Distributed Newton-Type Method for Gradient-Norm OptimizationCode0
Distance-Guided GA-Based Approach to Distributed Data-Intensive Web Service Composition—0
Real-time cortical simulations: energy and interconnect scaling on distributed systemsCode0
Communication-Efficient Policy Gradient Methods for Distributed Reinforcement Learning—0
DLHub: Model and Data Serving for Science—0
Partitioned Variational Inference: A unified framework encompassing federated and continual learning—0
Distributed Gradient Descent with Coded Partial Gradient Computations—0
Toward Creating Subsurface Camera—0
Communication Efficient Parallel Algorithms for Optimization on Manifolds—0
Quantile Regression Under Memory Constraint—0
A Bi-layered Parallel Training Architecture for Large-scale Convolutional Neural Networks—0
A Periodicity-based Parallel Time Series Prediction Algorithm in Cloud Computing Environments—0
A Droplet Approach Based on Raptor Codes for Distributed Computing With Straggling Servers—0
Predicate learning in neural systems: Discovering latent generative structures—0
Towards automated neural design: An open source, distributed neural architecture research framework—0
Left Ventricle Segmentation and Volume Estimation on Cardiac MRI using Deep Learning—0
PARyOpt: A software for Parallel Asynchronous Remote Bayesian Optimization—0
A MapReduce based Big-data Framework for Object Extraction from Mosaic Satellite Images—0
On the Effect of Task-to-Worker Assignment in Distributed Computing Systems with Stragglers—0
Orchestral: a lightweight framework for parallel simulations of cell-cell communicationCode0
Holographic Automata for Ambient Immersive A. I. via Reservoir Computing—0
Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process RegressionCode0
Predictive Performance Modeling for Distributed Computing using Black-Box Monitoring and Machine Learning—0
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