This paper concerns the generalizability of biometric identification results from small-sized closed systems to larger open systems. Many researchers have claimed high identificati...
Michael Gibbons, Sungsoo Yoon, Sung-Hyuk Cha, Char...
We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conjecture that it is intractable, but...
Background: An important aspect of protein design is the ability to predict changes in protein thermostability arising from single- or multi-site mutations. Protein thermostabilit...
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...