We present methods for inferring the cost of interrupting users based on multiple streams of events including information generated by interactions with computing devices, visual ...
Ideally pattern recognition machines provide constant output when the inputs are transformed under a group G of desired invariances. These invariances can be achieved by enhancing...
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...
Action rules introduced in [12] and extended further to e-action rules [21] have been investigated in [22], [13], [20]. They assume that attributes in a database are divided into t...
We develop a theory for learning scenarios where multiple learners co-exist but there are mutual compatibility constraints on their outcomes. This is natural in cognitive learning...