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Distributed Computing

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Showing 351–379 of 379 papers

TitleStatusHype
A Multi-Agent System Approach to Load-Balancing and Resource Allocation for Distributed Computing—0
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning:A Systematic StudyCode0
Tag-Weighted Topic Model For Large-scale Semi-Structured Documents—0
Splash: User-friendly Programming Interface for Parallelizing Stochastic Algorithms—0
CloudCV: Large Scale Distributed Computer Vision as a Cloud Service—0
Graph Partitioning via Parallel Submodular Approximation to Accelerate Distributed Machine Learning—0
An Asynchronous Mini-Batch Algorithm for Regularized Stochastic Optimization—0
Unwrapping ADMM: Efficient Distributed Computing via Transpose Reduction—0
RankMap: A Platform-Aware Framework for Distributed Learning from Dense DatasetsCode0
Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss—0
MLitB: Machine Learning in the BrowserCode0
Big Learning with Bayesian Methods—0
FGPGA: An Efficient Genetic Approach for Producing Feasible Graph Partitions—0
N^3LARS: Minimum Redundancy Maximum Relevance Feature Selection for Large and High-dimensional Data—0
Improved Distributed Principal Component Analysis—0
Online Asynchronous Distributed RegressionCode0
Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models—0
Chemlambda, universality and self-multiplication—0
A Survey on Dynamic Job Scheduling in Grid Environment Based on Heuristic Algorithms—0
Automated Reasoning in Modal and Description Logics via SAT Encoding: the Case Study of K(m)/ALC-Satisfiability—0
Structure-Aware Dynamic Scheduler for Parallel Machine Learning—0
Embed and Conquer: Scalable Embeddings for Kernel k-Means on MapReduce—0
Linearized Alternating Direction Method with Parallel Splitting and Adaptive Penalty for Separable Convex Programs in Machine Learning—0
On estimating total time to solve SAT in distributed computing environments: Application to the SAT@home project—0
Conditions for Convergence in Regularized Machine Learning Objectives—0
Link Prediction with Social Vector Clocks—0
Cellular Tree Classifiers—0
Distributed Matrix Completion and Robust Factorization—0
Computing High Accuracy Power Spectra with PicoCode0
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