[Lisa_seminaires] Predoc presentation of Saizheng Zhang

Aaron Courville aaron.courville at gmail.com
Lun 12 Sep 10:02:12 EDT 2016


Greeting,

Today (Monday Sept. 12th) at 1pm in AA3195 will be Saizheng Zhang predoc
presentation. Please come to support a fellow lab member.

Title: Understanding and Improving Recurrent Neural Networks

Abstract:

This predoctoral presentation will mainly focus on understanding and
exploring the properties of recurrent neural networks (RNNs) which are
proved to have strong capacities for modeling highly nonlinear dynamics in
sequential data. I will introduce two of my finished works on RNNs: In the
first work, I will talk about measuring the architectural complexity of the
general RNN structure, which is strongly related to RNN's connecting
topology. In the second work, I will talk about a general structural design
which is applicable for any popular recurrent structures (vanilla RNN,
LSTM, GRU, etc.). This structural design is extremely easy to implement and
can bring consistent performance improvement on a wide range of sequential
tasks.

Jury:

Président-rapporteur: Aaron Courville
Membre: Jian-Yun Nie
Directeur de Recherche: Yoshua Bengio
-- 
Aaron C. Courville
Département d’Informatique et
de recherche opérationnelle
Université de Montréal
email:Aaron.Courville at gmail.com
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