We present a manifold learning approach to dimensionality
reduction that explicitly models the manifold as a mapping
from low to high dimensional space. The manifold is
represen...
Tasks of data mining and information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be for...
Our goal is to fit the multiple instances (or structures) of a generic model existing in data. Here we propose a novel model selection scheme to estimate the number of genuine str...
Coreferencing entities across documents in a large corpus enables advanced document understanding tasks such as question answering. This paper presents a novel cross document core...
Jian Huang 0002, Sarah M. Taylor, Jonathan L. Smit...
An object-oriented neural network simulator kernel is presented. It is based on a general mathematical model for arbitrary feedforward nets. We propose a C++ implementation of thi...