Distributed Learning

Distributed Learning with Regularized Least Squares JMLR 2017 Distributed Mean Estimation with Limited Communication ICML 2017 Distributed Semi-supervised Learning with Kernel Ridge Regression JMLR 2017 Distributed Stochastic Variance Reduced Gradient Methods by Sampling Extra Data with Replacement JMLR 2017 Effective Parallelisation for Machine Learning NeurIPS 2017 Efficient Distributed Learning with Sparsity ICML 2017 Empirical Evaluation of Parallel Training Algorithms on Acoustic Modeling Interspeech 2017 Fast Parallel Training of Neural Language Models IJCAI 2017 Gaia: Geo-Distributed Machine Learning Approaching LAN Speeds NSDI 2017 Gradient Coding: Avoiding Stragglers in Distributed Learning ICML 2017 I Can’t Believe It’s Not Causal! Scalable Causal Consistency with No Slowdown Cascades NSDI 2017 Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network JMLR 2017 Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent NeurIPS 2017 Memory and Communication Efficient Distributed Stochastic Optimization with Minibatch Prox COLT 2017 Model Accuracy and Runtime Tradeoff in Distributed Deep Learning: A Systematic Study IJCAI 2017 On the Computational Complexity of Gossip Protocols IJCAI 2017 Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks ICML 2017 Parallel Streaming Wasserstein Barycenters NeurIPS 2017 PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference NeurIPS 2017 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 SCL: Simplifying Distributed SDN Control Planes NSDI 2017 See without looking: joint visualization of sensitive multi-site datasets IJCAI 2017 Sparse Communication for Distributed Gradient Descent EMNLP 2017