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...
This paper presents our practical experience of developing an ontology using the EXPLODE method for Value-Added Publishing. Value-Added Publishing is a relatively new area of elec...
A fundamental problem in distributed computing is performing a set despite failures and delays. Stated abstractly, the problem is to perform N tasks using P failure-prone processor...
Dariusz R. Kowalski, Mariam Momenzadeh, Alexander ...
Jackson networks have been very successful in so many areas in modeling parallel and distributed systems. However, the ability of Jackson networks to predict performance with syste...
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...