PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Fast Prediction on a Tree
Mark Herbster, Massimiliano Pontil and Sergio Rojas
In: NIPS 2008, 8-11 Dec 2008, Vancouver, Canada.

Abstract

Given an n-vertex weighted tree with structural diameter S and a subset of m vertices, we present a technique to compute a corresponding m × m Gram matrix of the pseudoinverse of the graph Laplacian in O(n + m^2 + mS) time. We discuss the application of this technique to fast label prediction on a generic graph. We approximate the graph with a spanning tree and then we predict with the kernel perceptron. We address the approximation of the graph with either a minimum spanning tree or a shortest path tree. The fast computation of the pseudoinverse enables us to address prediction problems on large graphs. We present experiments on two web-spam classification tasks, one of which includes a graph with 400,000 vertices and more than 10,000,000 edges. The results indicate that the accuracy of our technique is competitive with previous methods using the full graph information.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:5144
Deposited By:Mark Herbster
Deposited On:24 March 2009