Structured Input - Structured Output
Karsten Borgwardt · Koji Tsuda · Vishwanathan S V N · Xifeng Yan

Fri Dec 12th 07:30 AM -- 06:30 PM @ Hilton: Sutcliffe B
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Structured data emerges rapidly in a large number of disciplines: bioinformatics, systems biology, social network analysis, natural language processing and the Internet generate large collections of strings, graphs, trees, and time series. Designing and analysing algorithms for dealing with these large collections of structured data has turned into a major focus of machine learning over recent years, both in the input and output domain of machine learning algorithms, and is starting to enable exciting new applications of machine learning. The goal of this workshop is to bring together experts on learning with structured input and structured output domains and its applications, in order to exchange the latest developments in these growing fields. The workshop will include one session on learning with structured inputs, featuring a keynote by Prof. Eric Xing from Carnegie Mellon University. A second session will focus on learning with structured outputs, with a keynote by Dr. Yasemin Altun from the MPI for Biological Cybernetics. A third session will present novel applications of structured input-structured output learning to real-world problems.

Author Information

Karsten Borgwardt (ETH Zurich)

Karsten Borgwardt is Professor of Data Mining at ETH Zürich, at the Department of Biosystems located in Basel. His work has won several awards, including the NIPS 2009 Outstanding Paper Award, the Krupp Award for Young Professors 2013 and a Starting Grant 2014 from the ERC-backup scheme of the Swiss National Science Foundation. Since 2013, he is heading the Marie Curie Initial Training Network for "Machine Learning for Personalized Medicine" with 12 partner labs in 8 countries ( The business magazine "Capital" listed him as one of the "Top 40 under 40" in Science in/from Germany in 2014, 2015 and 2016. For more information, visit:

Koji Tsuda (University of Tokyo)
Vishwanathan S V N (National ICT Australia)
Xifeng Yan (IBM T. J. Watson Research Center)

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