This paper presents novel techniques for improving the performance of a multi-way spectral
clustering framework (Govindu in Proceedings of the 2005 IEEE Computer Society …

We resolve a basic problem on subspace distances that often arises in applications: How
can the usual Grassmann distance between equidimensional subspaces be extended to …

The ever-growing amount of data stored in digital databases raises the question of how to
organize and extract useful knowledge. This paper outlines some current developments in …

In this paper, we study the problem of predicting future citation count of a scientific article
after a given time interval of its publication. To this end, we gather and conduct an …

We propose a spectral clustering method based on local principal components analysis
(PCA). After performing local PCA in selected neighborhoods, the algorithm builds a nearest …

In the context of clustering, we assume a generative model where each cluster is the result
of sampling points in the neighborhood of an embedded smooth surface; the sample may be …

We study the reconstruction of a stratified space from a possibly noisy point sample.
Specifically, we use the vineyard of the distance function restricted to a 1-parameter family of …

Abstract The problem of Hybrid Linear Modeling (HLM) is to model and segment data using
a mixture of affine subspaces. Different strategies have been proposed to solve this problem …

The objective of this paper is to show that point cloud data can under certain circumstances
be clustered by strata in a plausible way. For our purposes, we consider a stratified space to …

A framework for the regularized and robust estimation of non-uniform dimensionality and
density in high dimensional noisy data is introduced in this work. This leads to learning …