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The SFB 876

A-Projects

Projects of type A unify research on embedded systems and data analysis. Algorithms developed here provide a basis for evaluation and application in other projects.

A1 - Data Mining for Ubiquitous System Software
A2 - Algorithmic aspects of learning methods in embedded systems
A3 - Methods for Efficient Resource Utilization in Machine Learning Algorithms
A4 - Resource efficient and distributed platforms for integrative data analysis
A5 - Exchange and Fusion of Information under Availability and Confidentiality Requirements in MultiAgent Systems
A6 - Resource efficient analysis of graphs

Here the resource constraints based on limitations of the device are in focus. In many cases, data distribution and therefore the need for fusion of data demand adaptation of established data mining processes.

B1 - Analysis of Spectrometry Data with Restricted Resources
B2 - Resource optimizing real time analysis of artifactious image sequences for the detection of nano objects
B3 - Data Mining on Sensor Data of Automated Processes
B4 - Analysis and Communication for dynamic traffic prognosis

C-Projects

Projects of part C deal with dynamic and high-dimensional data. From reliable selection of features to distributed regressions approaches are evaluated to deal with this type of resource constraint implied by the huge amount of data.

C1 - Feature selection in high-dimensional data for risk prognosis in oncology
C3 - Multi-level statistical analysis of high-frequency spatio-temporal process data
C4 - Regression approaches for large-scale high-dimensional data
C5 - Realtime Analysis and Storing of High Capacity Data in Particle Physics

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The SFB 876

A-Projects

B-Projects

C-Projects