We propose a Classification Via Clustering (CVC) algorithm which enables existing clustering methods to be efficiently employed in classification problems. In CVC, training and test data are coclustered and class-cluster distributions are used to find the label of the test data. To determine an efficient number of clusters, a Semi-supervised Hierarchical Clustering (SHC) algorithm is proposed. ...

We present a simple technique for detecting communities by utilizing both the link structure and folksonomy (or tag) information. A simple way to describe our approach is by defining a community as a set of nodes in a graph that link more frequently within this set than outside it and they share similar tags. Our technique is based on the Normalized Cut (NCut) algorithm and can be easily and ef...

We investigate axioms that intuitively ought to be satisfied by graph clustering objective functions. Two tailored for graph clustering objectives are introduced, and the four axioms introduced in previous work on distance based clustering are reformulated and generalized for the graph setting. We show that modularity, a standard objective for graph clustering, does not satisfy all these axioms...

This paper proposes a new evolutionary region merging method in order to efficiently improve segmentation quality results. Our approach starts from an oversegmented image, which is obtained by applying a standard morphological watershed transformation on the original image. Next, each resulting region is represented by its centroid. The oversegmented image is described by a simplified undirecte...

Perceptual organization refers to the ability to impose organization on sensory data, so as to group sensory primitives arising from a common underlying cause. The existence of this sort of organization in human perception, including vision, was emphasized by Gestalt psychologists. Since then, perceptual organization ideas have been found to be extremely useful in computer vision, impacting obj...

Abstract. Generally one encounters a substantial variation in the mechanical properties of composite laminates. This is due to the fact that a large number of parameters have to be controlled during the manufacturing process. The dispersion in the material properties can best be accounted for by modelling these as random. In this paper, FEM in conjunction with Monte Carlo Simulation is employed...

A recent theoretical analysis shows the equivalence between non-negative matrix factorization (NMF) and spectral clustering based approach to subspace clustering. As NMF and many of its variants are essentially linear, we introduce a nonlinear NMF with explicit orthogonality and derive general kernelbased orthogonal multiplicative update rules to solve the subspace clustering problem. In nonlin...

Given a graph, the sparsest cut problem asks for a subset of vertices whose edge expansion (the normalized cut given by the subset) is minimized. In this paper, we study a generalization of this problem seeking for k disjoint subsets of vertices (clusters) whose all edge expansions are small and furthermore, the number of vertices remained in the exterior of the subsets (outliers) is also small...