Add to ORKGAbstract. Recently, a novel graph-theoretic notion of a cluster has been proposed, i.e., the “dominant set”, which captures the two basic require-ments of a cluster, namely internal coherency and external incoherency. In this paper, we tackle the problem of finding several dominant sets using the replicator dynamics. Specifically, we adopt a game-theoretic perspective to this iterative extraction: Game dynamics are used to lo-cate individual dominant sets, and after each extraction the similarity matrix is transformed in such a way as to make the located cluster un-stable under the dynamics, without affecting the remaining groups. This guarantees that once found, a cluster will not be extracted again.
We develop a framework for the image segmentation problem based on a new graph-theoretic formulation...
In this paper, we develop a game theoretic approach for clustering features in a learning problem. F...
In this article we propose a new model for document clustering, based on game theoretic principles. ...
Clustering refers to the process of extracting maximally coherent groups from a set of objects using...
Pairwise (or graph-based) clustering algorithms typically assume the existence of a single affinity ...
Pairwise (or graph-based) clustering algorithms typically assume the existence of a single affinity ...
Clustering refers to the process of extracting maximally coherent groups from a set of objects using...
We develop a new graph-theoretic approach for pairwise data clustering which is motivated by the ana...
Hypergraph clustering refers to the process of extracting maximally coherent groups from a set of ob...
The field of pairwise clustering is currently domi-nated by the idea of dividing a set of objects in...
Recently dominant sets, a generalization of the notion of the maximal clique to edge-weighted graphs...
Clustering is a technique for discovering patterns and structure in data. Often, the most difficult ...
We propose a fast population game dynamics, motivated by the analogy with infection and immunization...
In this paper, we approach the classical problem of clustering using solution concepts from cooperat...
We develop a framework for the image segmentation problem based on a new graph-theoretic formulation...
In this paper, we develop a game theoretic approach for clustering features in a learning problem. F...
In this article we propose a new model for document clustering, based on game theoretic principles. ...
Clustering refers to the process of extracting maximally coherent groups from a set of objects using...
Pairwise (or graph-based) clustering algorithms typically assume the existence of a single affinity ...
Pairwise (or graph-based) clustering algorithms typically assume the existence of a single affinity ...
Clustering refers to the process of extracting maximally coherent groups from a set of objects using...
We develop a new graph-theoretic approach for pairwise data clustering which is motivated by the ana...
Hypergraph clustering refers to the process of extracting maximally coherent groups from a set of ob...
The field of pairwise clustering is currently domi-nated by the idea of dividing a set of objects in...
Recently dominant sets, a generalization of the notion of the maximal clique to edge-weighted graphs...
Clustering is a technique for discovering patterns and structure in data. Often, the most difficult ...
We propose a fast population game dynamics, motivated by the analogy with infection and immunization...
In this paper, we approach the classical problem of clustering using solution concepts from cooperat...
We develop a framework for the image segmentation problem based on a new graph-theoretic formulation...
In this paper, we develop a game theoretic approach for clustering features in a learning problem. F...
In this article we propose a new model for document clustering, based on game theoretic principles. ...