Züri ML #31: Machine Learning at Google Zurich

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Agenda

• 18:00 - Entrance

• 18:35 - Welcome

• 18:40 - Emmanuel Mogenet (confirmed): "ML Research @ Google ZH"

• 19:30 - Katja Filipova (confirmed): "Sentence compression by all means"

• 20:00 - Drinks & Discussion

• 21:00 - end

Emmanuel Mogenet onIntroduction on Machine intelligence at Google and its research organization in Europe

Bio: Emmanuel Mogenet is an Engineering Director who currently leads the ZRH-based Google European Research Lab.

Prior to his current role, Emmanuel led a team of 200+ engineers focused on improving various aspects of Google's search engine.

Before joining Google to work on Research and Search problems, Emmanuel spent most of his career working on solving 3D computer graphics and image processing problems for the film special effects industry. In particular, Emmanuel worked until 2006 at Apple Computers in California where he was part of the advanced image progressing group.

Emmanuel was born in 1967 in a small town in the south-east of France. He earned his Master’s degree in Computer Science and Artificial Intelligence in 1990 from the School of Mines of St-Etienne.

During the course of his career, Emmanuel lived and worked in Paris, Singapore, Tokyo, Los Angeles, and finally Zürich.

Katja Filippova on Sentence compression by all means: From pruning syntactic trees to generating zero-one sequences

Abstract: Text summarization has been a popular topic in the NLP research community because of the promise it holds for real-world applications and also because of its complexity: there are numerous scenarios where one would benefit from a technology to express the gist in a few words but doing so seems to require a lot of linguistic and world knowledge. In this talk I will give an overview of how sentence-level summarization, aka sentence compression, has been approached by our team in the past years and will describe an evolution from a syntax-based optimization algorithm to a syntax-free deep neural network.

Bio: Katja Filippova is a research scientist at Google. She holds a Ph.D. from the Technical University of Darmstadt (2009) and a MA from the University of Tübingen (2005). During her Ph.D. she was supported by the Klaus Tschira Foundation and was affiliated with the EML Research in Heidelberg (now the Heidelberg Institute for Theoretical Studies). She has worked on applying statistical methods to text understanding and generation.