batch normalization

On the Local Hessian in Back-propagation NeurIPS 2018 Regularizing by the Variance of the Activations' Sample-Variances NeurIPS 2018 Removing the Feature Correlation Effect of Multiplicative Noise NeurIPS 2018 Scalable methods for 8-bit training of neural networks NeurIPS 2018 Towards Understanding ECG Rhythm Classification Using Convolutional Neural Networks and Attention Mappings MLHC 2018 Understanding Batch Normalization NeurIPS 2018 Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models NeurIPS 2017 Deep Learning With Low Precision by Half-Wave Gaussian Quantization CVPR 2017 Improving Training of Deep Neural Networks via Singular Value Bounding CVPR 2017 On Calibration of Modern Neural Networks ICML 2017 On the Expressive Power of Deep Neural Networks ICML 2017 Revisit Fuzzy Neural Network: Demystifying Batch Normalization and ReLU with Generalized Hamming Network NeurIPS 2017 Riemannian approach to batch normalization NeurIPS 2017 Self-Normalizing Neural Networks NeurIPS 2017 The Shattered Gradients Problem: If resnets are the answer, then what is the question? ICML 2017 Train longer, generalize better: closing the generalization gap in large batch training of neural networks NeurIPS 2017 Advances in Very Deep Convolutional Neural Networks for LVCSR Interspeech 2016 Convolutional Neural Networks with Data Augmentation for Classifying Speakers’ Native Language Interspeech 2016 Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks ICML 2016 Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks NeurIPS 2016 Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift ICML 2015