distributed learning

Projection-free Distributed Online Learning in Networks ICML 2017 QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding NeurIPS 2017 Scalable Estimation of Dirichlet Process Mixture Models on Distributed Data IJCAI 2017 Sparse Communication for Distributed Gradient Descent EMNLP 2017 Tux²: Distributed Graph Computation for Machine Learning NSDI 2017 A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models ICML 2016 Asynchronous Parallel Learning for Neural Networks and Structured Models with Dense Features COLING 2016 Bootstrap Model Aggregation for Distributed Statistical Learning NeurIPS 2016 Communication Efficient Distributed Agnostic Boosting AISTATS 2016 DECOrrelated feature space partitioning for distributed sparse regression NeurIPS 2016 Distributed Clustering of Linear Bandits in Peer to Peer Networks ICML 2016 Distributed Multi-Task Learning AISTATS 2016 DSA: Decentralized Double Stochastic Averaging Gradient Algorithm JMLR 2016 d-VMP: Distributed Variational Message Passing PGM 2016 Feature-distributed sparse regression: a screen-and-clean approach NeurIPS 2016 Large Scale Distributed Semi-Supervised Learning Using Streaming Approximation AISTATS 2016 Latent Space Inference of Internet-Scale Networks JMLR 2016 Online and Distributed Bayesian Moment Matching for Parameter Learning in Sum-Product Networks AISTATS 2016 Scalable Gaussian Process Classification via Expectation Propagation AISTATS 2016 Training Neural Networks Without Gradients: A Scalable ADMM Approach ICML 2016 Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale NeurIPS 2016 Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization NeurIPS 2015 Communication Complexity of Distributed Convex Learning and Optimization NeurIPS 2015 Deep learning with Elastic Averaging SGD NeurIPS 2015 Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates JMLR 2015