[AI Seminar] Online AI Seminar on Nov 03 (Zoom) -- Aaron Courville -- Emerging and preserving compositional structure through iterated learning -- AI seminar is sponsored by Fortive

[Aayush Bansal]

Reminder...this is tomorrow at noon.

On Wed, Oct 28, 2020 at 8:05 AM Aayush Bansal <aayushb at cs.cmu.edu> wrote:

> Aaron Courville (University of Montreal) will be giving an
> online seminar on "Emerging and preserving compositional structure
> through iterated learning" from 12:00 noon - 01:00 PM ET on Nov 03.
>
> *Zoom Link*:
> https://cmu.zoom.us/j/99054050077?pwd=bjQ5OXN1Z09sQ3pVcTJDMVJBbjJkQT09
>
> CMU AI Seminar is sponsored by Fortive.
>
> Following are the details of the talk:
>
> *Title: *Emerging and preserving compositional structure through iterated
> learning
>
> *Abstract: *Iterated learning is a theory of how the compositional
> structure of human language emerged. The theory holds that
> intergenerational language transfer creates learning bottlenecks that
> privilege compositional structure. Recent work in the machine learning
> community has shown that the iterated learning mechanism can also promote
> compositional structure in language emergence in communication between
> neural-network-base AI-agents. In this talk, I will describe our recent
> efforts at putting iterated learning to work in applications of Neural
> Module Network to simple Visual Question Answering and in self-play
> training scenarios with dialogue models. We find that applying iterated
> learning to the generation of the program that specifies the assembly of
> distinct neural network modules leads to higher accuracy in program
> prediction and supports systematic generalization to testing question
> templates that are not in the training set. In the context of self-play
> training of dialogue agents, we find the surprising result that iterated
> learning can mitigate language drift.
>
>
> *Bio:* Aaron Courville is an Associate Professor in the Department of
> Computer Science and Operations Research at the Universite de Montreal. He
> received his PhD from the Robotics Institute, Carnegie Mellon University.
> He is one of the early contributors to Deep Learning, and is a founding
> member of Mila and a fellow of the CIFAR program on Learning in Machines
> and Brains. Together with Ian Goodfellow and Yoshua Bengio, he co-wrote the
> seminal textbook on Deep Learning. His current research interests focus on
> the development of DL models and methods. He is particularly interested in
> deep generative model and multimodal ML with applications such as computer
> vision and natural language processing. Aaron holds a CIFAR Canadian AI
> chair and his research is supported in part by Microsoft Research, Samsung,
> Hitachi, and a Google Focussed Research Award.
>
> To learn more about the seminar series, please visit the website:
> http://www.cs.cmu.edu/~aiseminar/
>
>
> --
> Aayush Bansal
> http://www.cs.cmu.edu/~aayushb/
>
>
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