Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
Karim T. Abou-Moustafa, Mohak Shah, Fernando De la...
In this paper, we define a family of syntactic kernels for automatic relational learning from pairs of natural language sentences. We provide an efficient computation of such mode...
This paper presents a unified image processing and analysis framework for cortical thickness in characterizing a clinical population. The emphasis is placed on the development of d...
We present a new approach for mapping natural language sentences to their formal meaning representations using stringkernel-based classifiers. Our system learns these classifiers ...
Distributional measures of lexical similarity and kernel methods for classification are well-known tools in Natural Language Processing. We bring these two methods together by int...