Machine Learning Blog

Monthly Archives: December 2016

Machine Learning seminar and discussion panel

News, Seminar.

19 Dec 2016, AG05, 2pm-5pm

Logic Tensor Networks, Knowledge Extraction and Applications


Ivan Donadello (FBK, Trento)

Adriana Danilakova (City, London)

Luciano Serafini (FBK, Trento)

Edjard Mota (UFAM, Manaus and City, London)

Simon Odense (City, London)

Dan Philps (Mondrian and City, London)

All are welcome!

Artur Garcez

ps. CoCo@NIPS’16 was a great workshop:

Research Seminar by Eric Humphrey from Spotify, NY

News, Seminar.

Who: Dr Eric Humphrey

When: Monday 5th Dec 2016, 16:00-17:00

Where: AG08 College Building, City, University of London

Title: Open-MIC – The Open Music Instrument Classification Challenge

 Abstract: The Open-MIC initiative is a community-driven experiment to benchmarking content-based MIR algorithms in a transparent and sustainable way. Eric will present the inspiration behind Open-MIC, the approach to building an open music dataset, and the engineering effort behind making the project work. Open-MIC is focused on music, but these topics that are widely applicable to general machine learning and signal processing evaluation.

 About the speaker: Eric Humphrey is a Senior Machine Learning Researcher at Spotify, focusing on algorithms and technology related to audio experience. He obtained a BSEE at Syracuse University in 2007, an MSc in Music Engineering Technology (U of Miami) in 2009 and a PhD in Music Technology at NYU in 2015. Eric is also a multi-instrumentalist, has been a visiting lecturer at the University of Miami, worked as an independent contractor roles for several audio technology companies, spent a summer at Google doing really fun things he can’t really talk about, and currently serves as the secretary to the International Society for Music Information Retrieval.


Data Bites seminar by Dirk Nachbar from Google

News, Seminar.

When: Tue, 6th Dec 2016, 1pm

Where: ELG04, City, University of London

Speaker: Dirk Nachbar (Google, marketing analytics)

Title: Analytical Problems in Marketing Science

Abstract: Like in many fields data is growing exponentially in marketing. I will describe four applications from the real world that use a lot of data and require modelling or data driven approaches: loyalty card data, online attribution problem, real time bidding/buying, and card linked marketing. The talk will introduce challenges and potential solutions in marketing and will describe the different players in the marketing ecosystem.

About the speaker: Dirk studied economics in Essex and then specialised in an MSc in Econometrics in Rotterdam. He worked across different sectors: retail, digital, loyalty, fintech. He worked for companies such as dunnhumby, Nielsen and is now Data Scientist at Google, where he measures effectiveness of advertising. In his spare time, he likes to code in Python, R, or Javascript as well using platforms such as Kaggle, Codewars.

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