In this paper we present a high-fidelity surface approximation technique that aims at a faithful reconstruction of piecewise-smooth surfaces from a scattered point set. The presen...
We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or...
ibe an abstract data model of protein structures by representing the geometry of proteins using spatial data types and present a framework for fast structural similarity search bas...
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...
We consider the problem of query containment over an object data model derived from F-logic. F-logic has generated considerable interest commercially, in the academia, and within ...