Abstract. This work proposes a family of language-independent semantic kernel functions defined for individuals in an ontology. This allows exploiting wellfounded kernel methods fo...
Kernel methods have gained a great deal of popularity in the machine learning community as a method to learn indirectly in highdimensional feature spaces. Those interested in rela...
Operating system research has endeavored to develop micro-kernels that provide modularity, reliability and security improvements over conventional monolithic kernels. However, the...
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
User applications that move a lot of data across the user-kernel boundary suffer from a serious performance penalty. We provide a framework, Compound System Calls (CoSy), to enhan...
Amit Purohit, Charles P. Wright, Joseph Spadavecch...