Recognition by Linear Combinations of Models
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part I
Recent directions in netlist partitioning: a survey
Integration, the VLSI Journal
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Factorization Approach to Grouping
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
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
A Unifying Approach to Hard and Probabilistic Clustering
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Non-negative tensor factorization with applications to statistics and computer vision
ICML '05 Proceedings of the 22nd international conference on Machine learning
Two-View Multibody Structure from Motion
International Journal of Computer Vision
SFCS '88 Proceedings of the 29th Annual Symposium on Foundations of Computer Science
Higher order learning with graphs
ICML '06 Proceedings of the 23rd international conference on Machine learning
Isotree: Tree clustering via metric embedding
Neurocomputing
Sparse Super Symmetric Tensor Factorization
Neural Information Processing
Spectral Curvature Clustering (SCC)
International Journal of Computer Vision
On d-dimensional d-semimetrics and simplex-type inequalities for high-dimensional sine functions
Journal of Approximation Theory
Spectral Clustering in Social-Tagging Systems
WISE '09 Proceedings of the 10th International Conference on Web Information Systems Engineering
International Journal of Computer Vision
Approximation algorithms for tensor clustering
ALT'09 Proceedings of the 20th international conference on Algorithmic learning theory
Ihara coefficients: a flexible tool for higher order learning
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Optimum subspace learning and error correction for tensors
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
A polynomial characterization of hypergraphs using the Ihara zeta function
Pattern Recognition
Automatic refinement of keyword annotations for web image search
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Hypergraph spectra for semi-supervised feature selection
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Hypergraph learning with hyperedge expansion
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Hypergraph spectra for unsupervised feature selection
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
A Scale Independent Selection Process for 3D Object Recognition in Cluttered Scenes
International Journal of Computer Vision
Hi-index | 0.00 |
We consider the problem of clustering data into k ≥ 2 clusters given complex relations — going beyond pairwise — between the data points. The complex n-wise relations are modeled by an n-way array where each entry corresponds to an affinity measure over an n-tuple of data points. We show that a probabilistic assignment of data points to clusters is equivalent, under mild conditional independence assumptions, to a super-symmetric non-negative factorization of the closest hyper-stochastic version of the input n-way affinity array. We derive an algorithm for finding a local minimum solution to the factorization problem whose computational complexity is proportional to the number of n-tuple samples drawn from the data. We apply the algorithm to a number of visual interpretation problems including 3D multi-body segmentation and illumination-based clustering of human faces.