The majority of theoretical work in machine learning is done under the assumption of exchangeability: essentially, it is assumed that the examples are generated from the same prob...
Vladimir Vovk, Ilia Nouretdinov, Alexander Gammerm...
In this paper, a multimedia data mining framework for discovering important but previously unknown knowledge such as vehicle identification, traffic flow, and the spatio-temporal ...
Tools to understand complex system behaviour are essential for many performance analysis and debugging tasks, yet there are many open research problems in their development. Magpi...
Paul Barham, Austin Donnelly, Rebecca Isaacs, Rich...
Self-tuning is a cost-effective and elegant solution to the important problem of configuring a database to the characteristics of the query load. Existing techniques operate in an...
Karl Schnaitter, Serge Abiteboul, Tova Milo, Neokl...
The challenge of monitoring massive amounts of data generated by communication networks has led to the interest in data stream processing. We study streams of edges in massive com...