The area of data stream algorithms has experienced a tremendous growth over the last decade; computing over continuous streams of data using only a limited amount of memory has become of key importance in many applications, including analysis of massive data sets and network monitoring. At the same time, the area has been enriched by the discovery of strong connections to other fields, such as randomized dimensionality reduction, metric embeddings, communication complexity and compressed sensing.
GOAL AND TOPICS
The goal of the summer school was to provide an in-depth introduction to some of the key issues in data stream computing, with the emphasis on theoretical tools for designing and analyzing efficient data stream algorithms. Specific topics include:
Algorithms for metric and geometric data streams
Randomized sketching and compressed sensing
Histograms, norms and other statistics of data streams
Algorithms for ordered data
Lower bounds and communication complexity
The topics was covered
by experts in the area.
lecturers from left:
Ravi Kumar (Yahoo!)
The summer school took place on August 20-23, 2007 at Center for Massive Data Algorithmics (MADALGO) in the Department of Computer Science, University of Aarhus, Denmark.
The school was targeted at graduate students, as well as researchers interested in an in-depth introduction to data stream algorithmics.
Registration was free; handouts, coffee breaks, lunches and a dinner were provided by MADALGO and the University of Aarhus.
Lars Arge (MADALGO, Aarhus)
Gerth S. Brodal (MADALGO, Aarhus)
Piotr Indyk (MADALGO, MIT)
Else Magård (MADALGO, Aarhus)
Center for MAssive Data ALGOrithmics, is a major new basic research center funded by the Danish National Research Foundation. The center is located at the Department of Computer Science, University of Aarhus, Denmark, but also includes researchers at CSAIL, Massachusetts Institute of Technology, USA, and at the Max Planck Institute for Informatics, Germany. The center covers all areas of the design, analysis and implementation of algorithms and data structures for processing massive data (interpreted broadly to cover computations where data is large compared to the computational resources), but initial focus will mainly be on I/O-efficient, cache-oblivious and data stream algorithms.
MADALGO - Center for Massive Data Algorithmics, a Center of the Danish National Research Foundation / Department of Computer Science / Aarhus University