Recent research has made significant progress on the problem of bounding log partition functions for exponential family graphical models. Such bounds have associated dual paramete...
Principal components analysis (PCA) is one of the most widely used techniques in machine learning and data mining. Minor components analysis (MCA) is less well known, but can also...
Max Welling, Felix V. Agakov, Christopher K. I. Wi...
In earlier work we have introduced and explored a variety of different probabilistic models for the problem of answering selectivity queries posed to large sparse binary data set...
Object-oriented technologies are frequently used to design and implement distributed applications. Object replication is a well-established approach to increase the dependability f...
In the early days a policy was a set of simple rules with a clear intuitive motivation that could be formalised to good effect. However the world is becoming much more complex. S...
Yow Tzu Lim, Pau-Chen Cheng, Pankaj Rohatgi, John ...