A good distance metric is crucial for unsupervised learning from high-dimensional data. To learn a metric without any constraint or class label information, most unsupervised metr...
We present PLIANT, a learning system that supports adaptive assistance in an open calendaring system. PLIANT learns user preferences from the feedback that naturally occurs during...
Melinda T. Gervasio, Michael D. Moffitt, Martha E....
Abstract. We study the problem of learning partitions using equivalence constraints as input. This is a binary classification problem in the product space of pairs of datapoints. ...
Abstract. In this paper we define the basic concepts for a general language for evolution and reactivity in the Semantic Web. We do this by exposing an UML model that specifies a...
Gene network reconstruction is a multidisciplinary research area involving data mining, machine learning, statistics, ontologies and others. Reconstructed gene network allows us t...