parallel computing

Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent NeurIPS 2017 Encoding, Fast and Slow: Low-Latency Video Processing Using Thousands of Tiny Threads NSDI 2017 Filter Flow Made Practical: Massively Parallel and Lock-Free CVPR 2017 Hardware-Efficient Guided Image Filtering for Multi-Label Problem CVPR 2017 MEC: Memory-efficient Convolution for Deep Neural Network ICML 2017 Tux²: Distributed Graph Computation for Machine Learning NSDI 2017 Cyclades: Conflict-free Asynchronous Machine Learning NeurIPS 2016 Distributed Coordinate Descent Method for Learning with Big Data JMLR 2016 FireCaffe: Near-Linear Acceleration of Deep Neural Network Training on Compute Clusters CVPR 2016 LIBMF: A Library for Parallel Matrix Factorization in Shared-memory Systems JMLR 2016 MLlib: Machine Learning in Apache Spark JMLR 2016 Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms ICML 2016 Parallel Majorization Minimization with Dynamically Restricted Domains for Nonconvex Optimization AISTATS 2016 Parallel Markov Chain Monte Carlo via Spectral Clustering AISTATS 2016 Robot Motion Planning on a Chip RSS 2016 Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale NeurIPS 2016 Deep learning with Elastic Averaging SGD NeurIPS 2015 Distributed Inference for Dirichlet Process Mixture Models ICML 2015 Distributed Matrix Completion and Robust Factorization JMLR 2015 Evolving GPU Machine Code JMLR 2015 On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants NeurIPS 2015 PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent ICML 2015 Asynchronous Anytime Sequential Monte Carlo NeurIPS 2014 Asynchronous Distributed ADMM for Consensus Optimization ICML 2014 Large-scale L-BFGS using MapReduce NeurIPS 2014