output
20132025
most citedZoneout: Regularizing RNNs by Randomly Preserving Hidden Activations

167 citations

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Showing 2017Show all

3 papers · 1 filter

stat.ML2017

Adaptive Stochastic Dual Coordinate Ascent for Conditional Random Fields

Rémi Le Priol, Alexandre Piché, Simon Lacoste-Julien

This work investigates the training of conditional random fields (CRFs) via the stochastic dual coordinate ascent (SDCA) algorithm of Shalev-Shwartz and Zhang (2016). SDCA enjoys a…

cs.CV2017★ 73 cited

Residual Connections Encourage Iterative Inference

Stanisław Jastrzębski, Devansh Arpit, Nicolas Ballas +3

Residual networks (Resnets) have become a prominent architecture in deep learning. However, a comprehensive understanding of Resnets is still a topic of ongoing research. A recent…

cs.LG2017

Parametric Adversarial Divergences are Good Losses for Generative Modeling

Gabriel Huang, Hugo Berard, Ahmed Touati +3

Parametric adversarial divergences, which are a generalization of the losses used to train generative adversarial networks (GANs), have often been described as being approximations…