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Distributed Learning

1100 directly classified papers

Papers per year

Papers

FireCaffe: Near-Linear Acceleration of Deep Neural Network Training on Compute Clusters CVPR 2016
TensorFlow: A System for Large-Scale Machine Learning OSDI 2016
Short-Dot: Computing Large Linear Transforms Distributedly Using Coded Short Dot Products NIPS 2016
Exploring the Hidden Dimension in Graph Processing OSDI 2016
Distributed Submodular Cover: Succinctly Summarizing Massive Data NIPS 2015
Communication Complexity of Distributed Convex Learning and Optimization NIPS 2015
Distributed Matrix Completion and Robust Factorization JMLR 2015
Distributed Box-Constrained Quadratic Optimization for Dual Linear SVM ICML 2015
Large-scale Distributed Dependent Nonparametric Trees ICML 2015
Parallelizing MCMC with Random Partition Trees NIPS 2015
FaLRR: A Fast Low Rank Representation Solver CVPR 2015
Secure Multi-party Differential Privacy NIPS 2015
SAMOA: Scalable Advanced Massive Online Analysis JMLR 2015
Deep learning with Elastic Averaging SGD NIPS 2015
Hashing for Distributed Data ICML 2015
Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates JMLR 2015
Adding vs. Averaging in Distributed Primal-Dual Optimization ICML 2015
Distributed Gaussian Processes ICML 2015
Extending Gossip Algorithms to Distributed Estimation of U-statistics NIPS 2015
The Power of Randomization: Distributed Submodular Maximization on Massive Datasets ICML 2015
DiSCO: Distributed Optimization for Self-Concordant Empirical Loss ICML 2015
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization NIPS 2015
Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation NIPS 2014
DFacTo: Distributed Factorization of Tensors NIPS 2014
Pitfalls in the use of Parallel Inference for the Dirichlet Process ICML 2014