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Moustapha Cissé

3 accepted papers

2018

Fooling End-To-End Speaker Verification With Adversarial Examples

ICASSP 2018accepted

Automatic speaker verification systems are increasingly used as the primary means to authenticate costumers. Recently, it has been proposed to train speaker verification systems using end-to-end deep neural models. In this paper, we show that such systems are vulnerable to adversarial example attack…

Cited by 0SourceScholar
2017

Efficient Softmax Approximation for GPUs

ICLR 2017workshop

We propose an approximate strategy to efficiently train neural network based language models over very large vocabularies. Our approach, called adaptive softmax, circumvents the linear dependency on the vocabulary size by exploiting the unbalanced word distribution to form clusters that explicitly m…

Cited by 348SourceScholar
2017

Efficient softmax approximation for GPUs

ICML 2017poster

We propose an approximate strategy to efficiently train neural network based language models over very large vocabularies. Our approach, called adaptive softmax, circumvents the linear dependency on the vocabulary size by exploiting the unbalanced word distribution to form clusters that explicitly m…