We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...
There are many machine learning algorithms currently available. In the 21st century, the problem no longer lies in writing the learner, but in choosing which learners to run on a ...
This paper explores unexpected results that lie at the intersection of two common themes in the KDD community: large datasets and the goal of building compact models. Experiments ...
This paper concerns the development of a new direction in machine learning, called natural induction, which requires from computergenerated knowledge not only to have high predicti...
We study the average number of well-chosen labeled examples that are required for a helpful teacher to uniquely specify a target function within a concept class. This "average...