How the Complexity in Datasets Pushes the Boundaries in ML Research

  • TYPE: Keynote DATE: Wednesday, November 27, 2019 TIME: 17:40-18:00 LOCATION: FORUM 12
Conference Agenda

The talk will explore the evolution of complexity in data sets and the evolution of complexity in the algorithms that deal with them. References will be made to simple datasets demonstrating simple machine learning models up to more complex datasets such as images, text and now non-euclidean datasets - such as point clouds, graphs, manifolds, geospatial datasets and network like data structures that represent highly complex interactions in systems-of-systems. The talk will also make references to a new family of powerful deep learning methods such as Graph neural networks and their applications to non-euclidean data domains. 


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Pooja is an engineer in Electronics and Communication with a post graduate degree in Systems and Signal processing from the University Of Southampton, UK. After her masters she worked in the biomedical industry in the UK for about 4 years. She worked at Equivital in Cambridge, UK as a Biomedical...


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AImpact Summit 2019

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  • Nov 27 - 28, 2019 Munich