We prove new lower bounds for learning intersections of halfspaces, one of the most important concept classes in computational learning theory. Our main result is that any statist...
This paper studies the complexity of learning classes of expressions in propositional logic from equivalence queries and membership queries. In particular, we focus on bounding th...
Marta Arias, Aaron Feigelson, Roni Khardon, Rocco ...
A standard approach in pattern classification is to estimate the distributions of the label classes, and then to apply the Bayes classifier to the estimates of the distributions in...
The general dimension is a combinatorial measure that characterizes the number of queries needed to learn a concept class. We use this notion to show that any p-evaluatable concep...
Abstract. Grammatical inference is typically defined as the task of finding a compact representation of a language given a subset of sample sequences from that language. Many di...