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Grounded Recurrent Neural Networks
Ankit Vani, Yacine Jernite, David Sontag
In this work, we present the Grounded Recurrent Neural Network (GRNN), a recurrent neural network architecture for multi-label prediction which explicitly ties labels to specific d…
Variable Computation in Recurrent Neural Networks
Yacine Jernite, Edouard Grave, Armand Joulin +1
Recurrent neural networks (RNNs) have been used extensively and with increasing success to model various types of sequential data. Much of this progress has been achieved through d…
Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation
Yacine Jernite, Anna Choromanska, David Sontag
We consider multi-class classification where the predictor has a hierarchical structure that allows for a very large number of labels both at train and test time. The predictive po…