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Stochastic Methods

97 papers

Papers per year

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Papers

LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning NIPS 2018
Statistical Tomography of Microscopic Life CVPR 2018
Accelerating Asynchronous Stochastic Gradient Descent for Neural Machine Translation EMNLP 2018
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks NIPS 2017
Reducing Reparameterization Gradient Variance NIPS 2017
Training Deep Networks without Learning Rates Through Coin Betting NIPS 2017
Differentiable Scheduled Sampling for Credit Assignment ACL 2017
Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters NIPS 2016
Distributed Flexible Nonlinear Tensor Factorization NIPS 2016
Using Spatial Order to Boost the Elimination of Incorrect Feature Matches CVPR 2016
Random Features for Sparse Signal Classification CVPR 2016
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization NIPS 2015
Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients NIPS 2015
Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms NIPS 2015
A Complete Recipe for Stochastic Gradient MCMC NIPS 2015
StopWasting My Gradients: Practical SVRG NIPS 2015
Variance Reduced Stochastic Gradient Descent with Neighbors NIPS 2015
Stochastic Proximal Gradient Descent with Acceleration Techniques NIPS 2014
Stochastic Optimization of PCA with Capped MSG NIPS 2013
Variance Reduction for Stochastic Gradient Optimization NIPS 2013
LSTD with Random Projections NIPS 2010
Simulated Annealing: Rigorous finite-time guarantees for optimization on continuous domains NIPS 2007