[Lisa_seminaires] [TeaTalk] Danny Tarlow, June 9, 13:45, AA5340

Dzmitry Bahdanau dimabgv at gmail.com
Ven 9 Juin 08:47:00 EDT 2017


Hi all,

Just a kind reminder about the talk :)

Dima

On Tue, 6 Jun 2017 at 15:22 Dzmitry Bahdanau <dimabgv at gmail.com> wrote:

> Hi all,
>
> You have just received an email about the tea-talk on June 13, but I have
> good news for you: we will have one more before that!
>
> Our next (really next) speaker is *Danny Tarlow*, who is a Research
> Scientist at Google Brain Montreal. He will present on *June 9, 13:45, at
> AA5340* (our usual tea-talk slot). Please find detailed information below.
>
> For those who are confused, the coming tea-talks will be given on June 9,
> 13 and 15 (yet to be announced).
>
> *Title:* Learning to Code: Machine Learning for Program Induction
>
> *Abstract:* I'll present two of our recent works on using machine
> learning ideas to induce computer programs from input-output examples. The
> first system is TerpreT, which casts program synthesis as a continuous
> optimization problem on which we perform gradient descent. It enables
> comparison of gradient-based program synthesis techniques to discrete
> search techniques that are popular in the programming languages community.
> Based on our learnings from TerpreT, we develop the second system,
> DeepCoder, which induces programs from input-output examples using a neural
> network to guide discrete search techniques. DeepCoder achieves an order of
> magnitude speedup over optimized search techniques, and it can solve
> problems of difficulty comparable to the very simplest problems on
> programming competition websites.
>
> *Bio:* Danny Tarlow is a Research Scientist at Google Brain Montreal. His
> main research interests are in the application of machine learning to
> problems involving structured data, with a specific interest in the
> intersection of machine learning and programming languages. He is a
> co-editor of the recent MIT Press book on Perturbations, Optimization, and
> Statistics (2017). His work has won awards at UAI (Best Student Paper,
> Runner Up), the ICML Workshop on Constructive Machine Learning (Best
> Paper), the NIPS Workshop on Neural Abstract Machines and Program Induction
> (Best Paper), and NIPS (Best Paper). He holds a Ph.D. from the Machine
> Learning group at the University of Toronto (2013) and previously was a
> Researcher at Microsoft Research Cambridge UK (2013 - 2017) with a Research
> Fellowship at Darwin College, University of Cambridge (2013 - 2016).
>
> Dima
>
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