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Structured Input - Structured Output

MPS-Authors
/persons/resource/persons75313

Borgwardt,  KM
Former Research Group Machine Learning and Computational Biology, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84265

Tsuda,  K
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

External Resource

http://media.nips.cc/Conferences/2008/NIPSWorkshopsProgram2008.pdf
(Abstract)

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Citation

Borgwardt, K., Tsuda, K., Vishwanathan, S., & Yan, X. (2008). Structured Input - Structured Output. Talk presented at NIPS 2008 Workshop: Structured Input - Structured Output (NIPS SISO 2008). Whistler, BC, Canada. 2008-12-12.


Cite as: https://hdl.handle.net/21.11116/0000-0003-A0AF-3
Abstract
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 struc-
tured 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 learn-
ing. 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 feature keynotes by Prof. Eric Xing from Carnegie Mellon University and by Dr Yasemin Altun from the MPI for Biological Cybernetics.