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...
In support vector machines (SVM), the kernel functions which compute dot product in feature space significantly affect the performance of classifiers. Each kernel function is suit...
We prove the statistical consistency of kernel Partial Least Squares Regression applied to a bounded regression learning problem on a reproducing kernel Hilbert space. Partial Lea...
We present a novel approach to parallel Boolean satisfiability (SAT) checking. A distinctive feature of our parallel SAT checker is that it incorporates all essential heuristics ...
Wolfgang Blochinger, Carsten Sinz, Wolfgang Kü...
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...