The paper presents a kernel for learning from ordered hypergraphs, a formalization that captures relational data as used in Inductive Logic Programming (ILP). The kernel generaliz...
We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
We present two results which arise from a model-based approach to hierarchical agglomerative clustering. First, we show formally that the common heuristic agglomerative clustering...
Sepandar D. Kamvar, Dan Klein, Christopher D. Mann...
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...