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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

Fast Probabilistic Optimization from Noisy Gradients ICML 2013
On the importance of initialization and momentum in deep learning ICML 2013
Accelerating Stochastic Gradient Descent using Predictive Variance Reduction NIPS 2013
Variance Reduction for Stochastic Gradient Optimization NIPS 2013
No more pesky learning rates ICML 2013
BudgetedSVM: A Toolbox for Scalable SVM Approximations JMLR 2013
Adaptive dropout for training deep neural networks NIPS 2013
Efficient Large-Scale Structured Learning CVPR 2013
Multi Kernel Learning with Online-Batch Optimization JMLR 2012
Krylov Subspace Descent for Deep Learning AISTATS 2012
Open Problem: Is Averaging Needed for Strongly Convex Stochastic Gradient Descent? COLT 2012
A Stochastic Gradient Method with an Exponential Convergence _Rate for Finite Training Sets NIPS 2012
Breaking the Curse of Kernelization: Budgeted Stochastic Gradient Descent for Large-Scale SVM Training JMLR 2012
Efficient Distributed Linear Classification Algorithms via the Alternating Direction Method of Multipliers AISTATS 2012
A Differentially Private Stochastic Gradient Descent Algorithm for Multiparty Classification AISTATS 2012
Toward a Noncommutative Arithmetic-geometric Mean Inequality: Conjectures, Case-studies, and Consequences COLT 2012
Stochastic Gradient Descent with Only One Projection NIPS 2012
Large Scale Distributed Deep Networks NIPS 2012
ImageNet Classification with Deep Convolutional Neural Networks NIPS 2012
Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities NIPS 2011
Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent NIPS 2011
Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning NIPS 2011
Relative Entropy Inverse Reinforcement Learning AISTATS 2011
Parallelized Stochastic Gradient Descent NIPS 2010
Optimal Web-Scale Tiering as a Flow Problem NIPS 2010