Abstract: Our main contribution is to propose a novel model selection methodology, expectation minimization of information criterion (EMIC). EMIC makes a significant impact on the...
The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image...
This paper proposes a validation approach, based on simulation, which addresses problems related to both state space explosion of formal methods and low coverage of informal metho...
Existing data embedding algorithms for polygonal meshes and their attributes can't be applied to the majority of (geometric) computer aided design (CAD) applications, for two...
Abstract. We propose a framework in which query sizes can be estimated from arbitrary statistical assertions on the data. In its most general form, a statistical assertion states t...