Autoassociator is an important issue in concept learning, and the learned concept of a particular class can be used to distinguish the class from the others. For nonlinear autoass...
In this paper, we propose a novel class of graphs, the tripartite directed acyclic graphs (tDAGs), to model first-order rule feature spaces for sentence pair classification. We in...
Many system-level design tasks (e.g. timing analysis, hardware/software partitioning and design space exploration) involve computational kernels that are intractable (usually NP-ha...
In this paper we investigate conditions on the features of a continuous kernel so that it may approximate an arbitrary continuous target function uniformly on any compact subset o...
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences...
Huma Lodhi, John Shawe-Taylor, Nello Cristianini, ...