Diffusion kernels on graphs and other discrete input spaces Export

@misc{citeulike:1884597, abstract = {The application of kernel-based learning algorithms has, so far, largely been confined to realvalued data and a few special data types, such as strings. In this paper we propose a general method of constructing natural families of kernels over discrete structures, based on the matrix exponentiation idea. In particular, we focus on generating kernels on graphs, for which we propose a special class of exponential kernels called diffusion kernels, which are based on the heat equation and ...}, author = {Kondor, R. and Lafferty, J.}, citeulike-article-id = {1884597}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.7612}, keywords = {algorithms, information\_retrieval, link\_analysis}, posted-at = {2009-03-01 09:36:52}, priority = {2}, title = {Diffusion kernels on graphs and other discrete input spaces}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.7612}, year = {2002} }

TY - GEN ID - citeulike:1884597 L3 - citeulike-article-id:1884597 N2 - The application of kernel-based learning algorithms has, so far, largely been confined to realvalued data and a few special data types, such as strings. In this paper we propose a general method of constructing natural families of kernels over discrete structures, based on the matrix exponentiation idea. In particular, we focus on generating kernels on graphs, for which we propose a special class of exponential kernels called diffusion kernels, which are based on the heat equation and ... TI - Diffusion kernels on graphs and other discrete input spaces KW - algorithms KW - information_retrieval KW - link_analysis AU - Kondor, R AU - Lafferty, J PY - 2002/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.7612 ER -