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1 accepted papers

2018

OLÉ: Orthogonal Low-Rank Embedding - A Plug and Play Geometric Loss for Deep Learning

CVPR 2018poster

Deep neural networks trained using a softmax layer at the top and the cross-entropy loss are ubiquitous tools for image classification. Yet, this does not naturally enforce intra-class similarity nor inter-class margin of the learned deep representations. To simultaneously achieve these two goals, d…