This work describes a novel quadratic formulation for solving the normalized cuts-based clustering problem as an alternative to spectral clustering ...

This work describes a novel quadratic formulation for solving the nor- malized cuts-based clustering problem as an alternative to spectral clustering approaches ...

In this work, we present an overview of recent developments on approaches to solve the NCC problem with no requiring the calculation of eigenvectors.

This paper develops a fast and effective algorithm that is guaranteed to converge on normalized cut tasks and expresses prior knowledge by linear ...

In this paper, we express prior knowledge by linear constraints on the solution, with the goal of min- imizing the normalized cut criterion with respect to ...

Quadratic Problem Formulation with Linear Constraints for Normalized Cut Clustering. Conference Paper. Full-text available. Nov 2014.

graph cuts [6], and quadratic problem formulations with linear constrains [7, 8]. In this paper, we propose a method based on a heuristic search carried out ...

Normalized cuts clustering with prior knowledge and a pre-clustering stage · Quadratic Problem Formulation with Linear Constraints for Normalized Cut Clustering.

Abstract. We present a set of clustering algorithms that identify cluster boundaries by searching for a hyperplanar gap in unlabeled data sets.

This work advocates a novel extension of the quadratic transform to the multidimensional ratio case, thereby recasting the fractional 0-1 NCut problem into a ...