Normalization Techniques in Training DNNs: Methodology, Analysis and Application

Gated Orthogonal Recurrent Units: On Learning to Forget

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Training Faster by Separating Modes of Variation in Batch-Normalized Models

(2019) Mahdi M. Kalayeh et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Orthogonal Deep Neural Networks

(2019) Shuai Li et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Optimization Methods for Large-Scale Machine Learning

(2018) Léon Bottou et al.   SIAM REVIEW

$L1$ -Norm Batch Normalization for Efficient Training of Deep Neural Networks

(2018) Shuang Wu et al.   IEEE Transactions on Neural Networks and Learning Systems

ImageNet Large Scale Visual Recognition Challenge

(2015) Olga Russakovsky et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Deep learning

(2015) Yann LeCun et al.   NATURE

Empirical Arithmetic Averaging Over the Compact Stiefel Manifold

(2012) Tetsuya Kaneko et al.   IEEE TRANSACTIONS ON SIGNAL PROCESSING

A feasible method for optimization with orthogonality constraints

(2012) Zaiwen Wen et al.   MATHEMATICAL PROGRAMMING