Stochastic Methods
119 papers
Papers per year
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2
1
2
1
7
5
4
10
16
9
21
16
7
10
7
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'25
Papers
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation
NeurIPS 2019
Fluctuation-dissipation relations for stochastic gradient descent
ICLR 2019
Making Asynchronous Stochastic Gradient Descent Work for Transformers
EMNLP 2019
Momentum-Based Variance Reduction in Non-Convex SGD
NeurIPS 2019
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning
AAAI 2019
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification and Local Computations
NeurIPS 2019
Quasi-hyperbolic momentum and Adam for deep learning
ICLR 2019
Reducing Noise in GAN Training with Variance Reduced Extragradient
NeurIPS 2019
Sampled Softmax with Random Fourier Features
NeurIPS 2019
Scalable and Efficient Pairwise Learning to Achieve Statistical Accuracy
AAAI 2019
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
NeurIPS 2019
Accelerating Asynchronous Stochastic Gradient Descent for Neural Machine Translation
EMNLP 2018
A Linear Speedup Analysis of Distributed Deep Learning with Sparse and Quantized Communication
NeurIPS 2018
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization
NeurIPS 2018
Don't Decay the Learning Rate, Increase the Batch Size
ICLR 2018
Evolutionary Stochastic Gradient Descent for Optimization of Deep Neural Networks
NeurIPS 2018
How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD
NeurIPS 2018
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning
NeurIPS 2018
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator
NeurIPS 2018
Statistical Tomography of Microscopic Life
CVPR 2018
Training Deep Models Faster with Robust, Approximate Importance Sampling
NeurIPS 2018
Differentiable Scheduled Sampling for Credit Assignment
ACL 2017
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks
NeurIPS 2017
Reducing Reparameterization Gradient Variance
NeurIPS 2017
Training Deep Networks without Learning Rates Through Coin Betting
NeurIPS 2017