Cloud Computing

82 papers with code • 0 benchmarks • 0 datasets

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Use these libraries to find Cloud Computing models and implementations
2 papers
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Most implemented papers

Agnostic Federated Learning

litian96/fair_flearn 1 Feb 2019

A key learning scenario in large-scale applications is that of federated learning, where a centralized model is trained based on data originating from a large number of clients.

SEN12MS -- A Curated Dataset of Georeferenced Multi-Spectral Sentinel-1/2 Imagery for Deep Learning and Data Fusion

chrieke/awesome-satellite-imagery-datasets 18 Jun 2019

The availability of curated large-scale training data is a crucial factor for the development of well-generalizing deep learning methods for the extraction of geoinformation from multi-sensor remote sensing imagery.

Optimizing Deep Learning Recommender Systems' Training On CPU Cluster Architectures

hfp/libxsmm 10 May 2020

During the last two years, the goal of many researchers has been to squeeze the last bit of performance out of HPC system for AI tasks.

Acting in Delayed Environments with Non-Stationary Markov Policies

galdl/rl_delay_basic ICLR 2021

We introduce a framework for learning and planning in MDPs where the decision-maker commits actions that are executed with a delay of $m$ steps.

VMAgent: Scheduling Simulator for Reinforcement Learning

mail-ecnu/vmagent 9 Dec 2021

A novel simulator called VMAgent is introduced to help RL researchers better explore new methods, especially for virtual machine scheduling.

Forecasting Workload in Cloud Computing: Towards Uncertainty-Aware Predictions and Transfer Learning

andreareds/towardsuncertaintyawareworkloadprediction 24 Feb 2023

Results show that modelling the uncertainty of predictions has a positive impact on performance, especially on service level metrics, because uncertainty quantification can be tailored to desired target service levels that are critical in cloud applications.

Large-scale Artificial Neural Network: MapReduce-based Deep Learning

sunkairan/MapReduce-Based-Deep-Learning 9 Oct 2015

Faced with continuously increasing scale of data, original back-propagation neural network based machine learning algorithm presents two non-trivial challenges: huge amount of data makes it difficult to maintain both efficiency and accuracy; redundant data aggravates the system workload.

CLARIN-EL Web-based Annotation Tool

iit-Demokritos/clarin-el-annotation-tool LREC 2016

This paper presents a new Web-based annotation tool, the {``}CLARIN-EL Web-based Annotation Tool{''}.

DeepFood: Deep Learning-Based Food Image Recognition for Computer-Aided Dietary Assessment

deercoder/DeepFood 17 Jun 2016

We applied our proposed approach to two real-world food image data sets (UEC-256 and Food-101) and achieved impressive results.