About
The summer school includes lectures on predictive modelling methods for big and complex data. More specifically, the lectures present methods handling the following complexity aspects: (a) structured data as input or output of the prediction process, (b) very large/massive datasets, with many examples and/or many input/output dimensions, where data may be streaming at high rates, (c) incompletely/partially labelled data, and (d) data placed in a spatio-temporal or network context. Each of these is a major challenge to current ML/DM approaches and is the central topic of active research in areas such as structured-output prediction, mining data streams, semi-supervised learning, and mining network data. The applicability and the potential of the presented methods will be demonstrated on several showcases from molecular biology, sensor networks, multimedia, and social networks.
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Uploaded videos:
Opening and introduction
An Introduction to Mining Big and Complex Data
Jan 31, 2017
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1183 Views
Talks
Semi-supervised tree learning
Jan 31, 2017
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1446 Views
Kernel methods for structured data
Jan 31, 2017
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1044 Views
Semi-supervised learning for SOP
Jan 31, 2017
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890 Views
Metagenomics data analysis
Jan 31, 2017
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1002 Views
Multi-label learning from batch and streaming data
Jan 31, 2017
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1013 Views
Decomposition and structuring of the output space
Jan 31, 2017
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1101 Views
Ontology of Data Mining
Jan 31, 2017
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1013 Views
Mars Express Power Challenge
Jan 31, 2017
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921 Views
Mining network data
Jan 31, 2017
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1209 Views
Network reconstruction
Jan 31, 2017
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1085 Views
Mining tensor data
Jan 31, 2017
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1629 Views
Complex Networks Analysis
Jan 31, 2017
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1160 Views
Mining streaming data and networks
Jan 31, 2017
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1229 Views
Structured Output Prediction on Data Streams
Jan 31, 2017
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992 Views
Architectures for distributed mining of big data
Jan 31, 2017
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1263 Views
Network Applications
Jan 31, 2017
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987 Views
Spatio-temporal data mining: Part 1
Jan 31, 2017
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1036 Views
Spatio-temporal data mining: Part 2
Jan 31, 2017
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1199 Views
Large Scale Image Retrieval and Mining
Jan 31, 2017
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1245 Views
Sparse Estimation for Image and Vision Processing
Jan 31, 2017
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1318 Views
Towards deep kernel machines
Jan 31, 2017
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1368 Views
Deep learning for plant identification
Jan 31, 2017
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1152 Views
Selective Inference and the False Discovery Rate
Jan 31, 2017
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1189 Views
Redescription mining and its applications
Jan 31, 2017
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905 Views
Closing remarks
Selected Environmental Appplications Of Structured Output Prediction
Jan 31, 2017
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1080 Views