Self-explaining has been repeatedly shown to result in positive learning outcomes for students in a wide variety of disciplines. However, there are two potential accounts for why s...
We consider a natural framework of learning from correlated data, in which successive examples used for learning are generated according to a random walk over the space of possibl...
Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, Andr...
Disproof can be as important as proof in studying programs and programming languages. In particular, side conditions in a statement about program behavior are sometimes best unders...
We present in this paper a new learning problem called learning distributions from experts. In the case we study the experts are stochastic deterministic finite automata (sdfa). W...
We show our approach for the definition of Domain Specific Languages integrating both graphical and textual views. The approach is based on the meta-modelling concepts provided by ...