Fakultät Informatik


Kolloq. Cédric Archambeau, topic: Amazon: A Playground for Machine Learning

Tuesday, 20th of December 2016, 2:00 pm FMI HS 1 (MI-Building, Campus Garching)

Within Amazon, a company with over 200 million active consumers, over 2 million active seller accounts and over 180.000 employees, there are hundreds of problems which can be tackled using machine learning. In the first part of this talk, I will give an overview of a number of machine learning applications and explain how they fit within the Amazon ecosystem. While machine learning is routinely used in recommendation, fraud detection and ad allocation, it plays a key role in devices such as the Kindle or the Echo, as well as the automation of Kiva enabled fulfilment centres, statistical machine translation or automated Fresh produce inspection. In the second part, I will discuss how we democratise machine learning at Amazon. While machine learning enables us to learn predictive models from data, it requires careful tuning of so-called hyperparameters (e.g., learning rates or the amount of regularisation) to ensure good generalisation capabilities. As of today, the tuning of hyperparameters is done in an ad hoc fashion or manually. We adopted a principled approach based on Bayesian optimisation which enables us to automate this process. In effect, Bayesian optimisation sits on top of machine learning, materialising machine intelligence by taking the human out of the loop when building machine learning applications.

Cédric Archambeau is a Senior Machine Learning Scientist with Amazon, Berlin. He is the technical lead on the Machine Learning Platform & Applications team and served as a scientific advisor to Sebastian Gunningham, Amazon Senior Vice President Seller Services. Recently, his team delivered the learning algorithms offered in Amazon Machine Learning (https://aws.amazon.com/machine-learning), which is part of Amazon AI (https://aws.amazon.com/amazon-ai). He is interested in large scale probabilistic inference, Bayesian optimization and machine reasoning. He holds a visiting position in the Centre for Computational Statistics and Machine Learning at University College London. Prior to joining Amazon, he was managing the Machine Learning and Mechanism Design area at Xerox Research Centre Europe, Grenoble.

contact person:
Stephan Günnemann
Phone: +
Email: guennemann(at)in.tum.de



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