Recognition and Shape Synthesis of 3-D Objects Based on Attributed Hypergraphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spectra, Euclidean representations and clusterings of hypergraphs
Discrete Mathematics
Spectra of regular graphs and hypergraphs and orthogonal polynomials
European Journal of Combinatorics
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Multilinear Analysis of Image Ensembles: TensorFaces
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Clustering categorical data: an approach based on dynamical systems
The VLDB Journal — The International Journal on Very Large Data Bases
Discriminant Analysis with Tensor Representation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A Tensor Decomposition for Geometric Grouping and Segmentation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Image clustering with tensor representation
Proceedings of the 13th annual ACM international conference on Multimedia
Higher order learning with graphs
ICML '06 Proceedings of the 23rd international conference on Machine learning
A study of graph spectra for comparing graphs and trees
Pattern Recognition
Spectral Embedding of Feature Hypergraphs
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Spectral Curvature Clustering (SCC)
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Foundations of a Multi-way Spectral Clustering Framework for Hybrid Linear Modeling
Foundations of Computational Mathematics
Hypergraphs, Characteristic Polynomials and the Ihara Zeta Function
CAIP '09 Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns
Detecting the Number of Clusters in n-Way Probabilistic Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-way clustering using super-symmetric non-negative tensor factorization
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
A jensen-shannon kernel for hypergraphs
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
| Hi-index | 0.01 |
The aim of this paper is to seek a compact characterization of irregular unweighted hypergraphs for the purposes of clustering. To this end, we develop a polynomial characterization for hypergraphs based on the Ihara zeta function. We investigate the flexibility of the polynomial coefficients for learning relational structures with different relational orders. Furthermore, we develop an efficient method for computing the coefficient set. Our representation for hypergraphs takes into account not only the vertex connections but also the hyperedge cardinalities, and thus can distinguish different relational orders, which is prone to ambiguity if the hypergraph Laplacian is used. In our experimental evaluation, we demonstrate the effectiveness of the proposed characterization for clustering irregular unweighted hypergraphs and its advantages over the spectral characterization of the hypergraph Laplacian.