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stochastic gradient descent

1088 papers

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Also known as

SGD ASGD SAGA SGM SGDA PSGD SKGD

Co-occurring keywords

non-convex optimization (546) distributed learning (563) neural network optimization (1293) convergence rate (606) convex optimization (1320) neural network (6616) variance reduction (520) stochastic optimization (1060) convergence analysis (394) differential privacy (1010)

Papers

Parameters as interacting particles: long time convergence and asymptotic error scaling of neural networks NIPS 2018
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent NIPS 2017
Stochastic Online Anomaly Analysis for Streaming Time Series IJCAI 2017
Empirical Evaluation of Parallel Training Algorithms on Acoustic Modeling INTERSPEECH 2017
Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization IJCAI 2017
Large-scale Online Kernel Learning with Random Feature Reparameterization IJCAI 2017
Stochastic Modified Equations and Adaptive Stochastic Gradient Algorithms ICML 2017
Automated Inference with Adaptive Batches AISTATS 2017
Stochastic Generative Hashing ICML 2017
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling ACL 2017
Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization NIPS 2017
Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples NIPS 2017
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding NIPS 2017
Non-convex Finite-Sum Optimization Via SCSG Methods NIPS 2017
Mini-batch Block-coordinate based Stochastic Average Adjusted Gradient Methods to Solve Big Data Problems ACML 2017
Train longer, generalize better: closing the generalization gap in large batch training of neural networks NIPS 2017
Conditional Accelerated Lazy Stochastic Gradient Descent ICML 2017
Collaborative Deep Learning in Fixed Topology Networks NIPS 2017
Convergence Analysis of Two-layer Neural Networks with ReLU Activation NIPS 2017
Conjugate-Computation Variational Inference : Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models AISTATS 2017
Sparse Communication for Distributed Gradient Descent EMNLP 2017
Backstitch: Counteracting Finite-Sample Bias via Negative Steps INTERSPEECH 2017
Stochastic Gradient Descent as Approximate Bayesian Inference JMLR 2017
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning: A Systematic Study IJCAI 2017
Forward and Reverse Gradient-Based Hyperparameter Optimization ICML 2017