Abstract. This paper addresses the problem of clustering images of objects seen from different viewpoints. That is, given an unlabelled set of images of n objects, we seek an unsup...
In recent years, a fundamental problem structure has emerged as very useful in a variety of machine learning applications: Submodularity is an intuitive diminishing returns proper...
A large number of learning algorithms, for example, spectral clustering, kernel Principal Components Analysis and many manifold methods are based on estimating eigenvalues and eig...
A method is presented for identifying individuals by shape, given a sequence of noisy silhouettes segmented from video. A spectral partitioning framework is used to cluster similar...
In previous research in automatic verb classification, syntactic features have proved the most useful features, although manual classifications rely heavily on semantic features. ...