conftrace_

learning rate

192 papers

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Also known as

LR

Co-occurring keywords

stochastic gradient descent (1091) neural network optimization (1293) gradient descent (1144) convergence rate (607) convergence analysis (395) stochastic optimization (1060) online learning (1777) kernel methods (1097) neural network (6616) regret bound (1926)

Papers

Optimal Rates for Multi-pass Stochastic Gradient Methods JMLR 2017
Fast learning rates with heavy-tailed losses NIPS 2016
On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability NIPS 2016
Learning under uncertainty: a comparison between R-W and Bayesian approach NIPS 2016
Scaling-up Empirical Risk Minimization: Optimization of Incomplete $U$-statistics JMLR 2016
On the Influence of Momentum Acceleration on Online Learning JMLR 2016
Optimal Learning Rates for Localized SVMs JMLR 2016
Optimal Learning for Multi-pass Stochastic Gradient Methods NIPS 2016
MetaGrad: Multiple Learning Rates in Online Learning NIPS 2016
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift ICML 2015
Second-order Quantile Methods for Experts and Combinatorial Games COLT 2015
Learning from Data with Heterogeneous Noise using SGD AISTATS 2015
Learning the Learning Rate for Prediction with Expert Advice NIPS 2014
From Stochastic Mixability to Fast Rates NIPS 2014
Adaptive Step-Size for Policy Gradient Methods NIPS 2013
The Fast Convergence of Incremental PCA NIPS 2013
No more pesky learning rates ICML 2013
Optimal rates for stochastic convex optimization under Tsybakov noise condition ICML 2013
Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n) NIPS 2013
An Adaptive Learning Rate for Stochastic Variational Inference ICML 2013
Large-Scale Learning with Less RAM via Randomization ICML 2013
Fast Learning Rate of Multiple Kernel Learning: Trade-Off between Sparsity and Smoothness AISTATS 2012
Consistency and Rates for Clustering with DBSCAN AISTATS 2012
Optimal learning rates for least squares SVMs using Gaussian kernels NIPS 2011
Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning NIPS 2011