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Machine learning has historically been successful at dealing with structured datasets, such as tabular data. With recent advances, particularly in deep learning, there are now also well-established and powerful methods for working with image, text and speech data.

However, a lot of real-world data does not easily fit into one of these categories. One important class of such data is network or graph data, which can be used to model concepts such as social networks, transaction flow, computer networks and even molecular interactions. Using graphs we can easily represent and capture the complex interactions and dependencies between objects, but it also opens up a question: How can we apply machine learning to graph structured data?

Join us for this meetup, where we will explore the topic of machine learning on graphs with the help of our expert speakers.

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Agenda:

6:30pm - 6:45pm Meet, greet & welcome

6:45pm - 7:45pm

Speakers:
- "Deep Learning on Graphs", Xavier Bresson, Associate Professor in Computer Science at NTU. He is a leading researcher in the field of Graph Deep Learning, a new framework that combines graph theory and deep learning techniques to tackle complex data in multiple domains. The purpose of this talk is to introduce convolutional neural networks architectures on graphs, as well as applications for this class of problems.

- "Statistical Learning Problems on Graphs", Jonathan Scarlett, Assistant Professor in Computer Science and Mathematics at NUS. His research interests are in the areas of machine learning, information theory, and high-dimensional statistics, including graph learning. This talk will discuss statistical learning problems consisting of both the learning of graphs and learning from graphs, along with some popular algorithms and their applications.

7:45pm - Networking

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Organiser:

This event is organised by QuantumBlack

QuantumBlack is an advanced analytics firm operating at the intersection of strategy, technology and design to improve performance outcomes for organisations.

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Notice:

By participating in the meetup you agree that McKinsey & Company may (i) videotape, audiotape, photograph, or otherwise record your name, voice, or image, and (ii) use and distribute such videotapes, audiotapes, photographs or recordings of your name, voice or image in any texts, videos, and other materials that McKinsey may make available through websites and social media to its employees or any third parties.

If you do not wish to be recorded please inform the event organiser in advance.