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

Lipschitz Adaptivity with Multiple Learning Rates in Online Learning COLT 2019
When can unlabeled data improve the learning rate? COLT 2019
Sharp Analysis of Learning with Discrete Losses AISTATS 2019
Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach AISTATS 2019
Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise ICML 2019
Localized Structured Prediction NIPS 2019
Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks NIPS 2019
Control Batch Size and Learning Rate to Generalize Well: Theoretical and Empirical Evidence NIPS 2019
Using Statistics to Automate Stochastic Optimization NIPS 2019
Understanding the Role of Momentum in Stochastic Gradient Methods NIPS 2019
Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning NIPS 2019
Interaction Matters: A Note on Non-asymptotic Local Convergence of Generative Adversarial Networks AISTATS 2019
Understanding Batch Normalization NIPS 2018
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization ICML 2018
But How Does It Work in Theory? Linear SVM with Random Features NIPS 2018
Adaptive Methods for Nonconvex Optimization NIPS 2018
L4: Practical loss-based stepsize adaptation for deep learning NIPS 2018
Demystifying excessively volatile human learning: A Bayesian persistent prior and a neural approximation NIPS 2018
How SGD Selects the Global Minima in Over-parameterized Learning: A Dynamical Stability Perspective NIPS 2018
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption ICML 2018
Training Deep Networks without Learning Rates Through Coin Betting NIPS 2017
Distributed Learning with Regularized Least Squares JMLR 2017
Boltzmann Exploration Done Right NIPS 2017
Generalization Properties of Learning with Random Features NIPS 2017
Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network JMLR 2017