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Softmax function

Known as: Normalized exponential, Softmax, Softmax activation function 
In mathematics, in particular probability theory and related fields, the softmax function, or normalized exponential, is a generalization of the… Expand
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Papers overview

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Highly Cited
2018
Highly Cited
2018
In this letter, we propose a conceptually simple and intuitive learning objective function, i.e., additive margin softmax, for… Expand
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Highly Cited
2017
Highly Cited
2017
We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC… Expand
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Highly Cited
2017
Highly Cited
2017
Categorical variables are a natural choice for representing discrete structure in the world. However, stochastic neural networks… Expand
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Highly Cited
2017
Highly Cited
2017
This paper addresses deep face recognition (FR) problem under open-set protocol, where ideal face features are expected to have… Expand
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Highly Cited
2016
Highly Cited
2016
Recent applications of Convolutional Neural Networks (ConvNets) for human action recognition in videos have proposed different… Expand
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Highly Cited
2013
Highly Cited
2013
The recently introduced continuous Skip-gram model is an efficient method for learning high-quality distributed vector… Expand
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Highly Cited
2012
Highly Cited
2012
Gaussian mixture models are currently the dominant technique for modeling the emission distribution of hidden Markov models for… Expand
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Highly Cited
2010
Highly Cited
2010
We describe a method of incorporating task-specific cost functions into standard conditional log-likelihood (CLL) training of… Expand
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Highly Cited
2010
Highly Cited
2010
We describe a "log-bilinear" model that computes class probabilities by combining an input vector multiplicatively with a vector… Expand
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Highly Cited
1989
Highly Cited
1989
  • J. Bridle
  • NATO Neurocomputing
  • 1989
  • Corpus ID: 59636530
We are concerned with feed-forward non-linear networks (multi-layer perceptrons, or MLPs) with multiple outputs. We wish to treat… Expand
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