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Normalization

341 directly classified papers

Papers per year

Papers

Removing the Feature Correlation Effect of Multiplicative Noise NIPS 2018
Understanding Batch Normalization NIPS 2018
DropBlock: A regularization method for convolutional networks NIPS 2018
Understanding Weight Normalized Deep Neural Networks with Rectified Linear Units NIPS 2018
How Does Batch Normalization Help Optimization? NIPS 2018
On the Local Hessian in Back-propagation NIPS 2018
Inference-Invariant Transformation of Batch Normalization for Domain Adaptation of Acoustic Models INTERSPEECH 2018
Batch Normalized Deep Boltzmann Machines ACML 2018
Regularizing by the Variance of the Activations' Sample-Variances NIPS 2018
Improving Deep Neural Network Sparsity through Decorrelation Regularization IJCAI 2018
Dropout as a Low-Rank Regularizer for Matrix Factorization AISTATS 2018
Investigation on the Combination of Batch Normalization and Dropout in BLSTM-based Acoustic Modeling for ASR INTERSPEECH 2018
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks ICML 2018
On the Implicit Bias of Dropout ICML 2018
The Shattered Gradients Problem: If resnets are the answer, then what is the question? ICML 2017
On Calibration of Modern Neural Networks ICML 2017
Train longer, generalize better: closing the generalization gap in large batch training of neural networks NIPS 2017
Riemannian approach to batch normalization NIPS 2017
Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization NIPS 2017
Variational Dropout Sparsifies Deep Neural Networks ICML 2017
Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models NIPS 2017
Improving Training of Deep Neural Networks via Singular Value Bounding CVPR 2017
Surprising properties of dropout in deep networks COLT 2017
Dynamic Layer Normalization for Adaptive Neural Acoustic Modeling in Speech Recognition INTERSPEECH 2017
ConvNets with Smooth Adaptive Activation Functions for Regression AISTATS 2017