[Lisa_seminaires] Anirudh Goyal, September 15, AA6214, 11AM

Dzmitry Bahdanau dimabgv at gmail.com
Ven 15 Sep 09:40:34 EDT 2017


Hi all,

Just a kind reminder that this talk will take place today!

Dima

On Wed, 13 Sep 2017 at 17:20 Michael Noukhovitch <mnoukhov at gmail.com> wrote:

> Hi All!
>
> Dima is going on an internship so I'll be organizing tea talks for the
> next couple of months!
>
> This week, our very own *Anirudh* will present his NIPS paper (congrats
> btw!) it will be at *AA6214 on Friday September 15th, 11AM *Hope to see
> everyone there!
>
> *Title:* Z-Forcing: Training Stochastic Recurrent Networks
>
> *Abstract:* Many efforts have been devoted to training generative latent
> variable models with autoregressive decoders, such as recurrent neural
> networks (RNN). Stochastic recurrent models have been successful in
> capturing the variability observed in natural sequential data such as
> speech. We propose a novel sequential latent variable model unifying
> successful ideas from recently proposed architectures: each step in the
> sequence is associated with a latent variable that is used to condition the
> recurrent dynamics for future steps. Training is performed with amortised
> variational inference where the approximate posterior is augmented with a
> RNN that runs backward through the sequence. In addition to maximizing the
> variational lower bound, we ease training of the latent variables by adding
> an auxiliary cost which forces them to reconstruct the state of the
> backward recurrent network. This provides the latent variables with a
> task-independent objective that enhances the performance of the overall
> model. Although being conceptually simple, our model achieves
> state-of-the-art results on standard speech benchmarks such as TIMIT and
> BLIZZARD and competitive performance on sequential MNIST. Finally, we apply
> our model on language modeling in the IMDB dataset. The auxiliary cost is
> crucial for learning interpretable latent variables.
>
> Michael
>
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