Multiway clustering of 3-order tensor via affinity matrix

We propose a new method of multiway clustering for 3-order tensors via affinity matrix (MCAM). Based on a notion of similarity between the tensor slices and the spread of information of each slice, our model builds an affinity/similarity matrix on which we apply advanced clustering methods. The combination of all clusters of the three modes delivers the desired multiway clustering. Finally, MCAM achieves competitive results compared with other known algorithms on synthetics and real datasets.

READ FULL TEXT
research
09/22/2021

Multi-Slice Clustering for 3-order Tensor Data

Several methods of triclustering of three dimensional data require the s...
research
09/09/2022

Affinity-VAE for disentanglement, clustering and classification of objects in multidimensional image data

In this work we present affinity-VAE: a framework for automatic clusteri...
research
09/09/2021

Compositional Affinity Propagation: When Clusters Have Compositional Structure

We consider a new kind of clustering problem in which clusters need not ...
research
01/13/2021

Improved Hierarchical Clustering on Massive Datasets with Broad Guarantees

Hierarchical clustering is a stronger extension of one of today's most i...
research
05/10/2019

Integrating Tensor Similarity to Enhance Clustering Performance

Clustering aims to separate observed data into different categories. The...
research
02/09/2022

Application of the Affinity Propagation Clustering Technique to obtain traffic accident clusters at macro, meso, and micro levels

Accident grouping is a crucial step in identifying accident-prone locati...
research
02/03/2023

Uniform tensor clustering by jointly exploring sample affinities of various orders

Conventional clustering methods based on pairwise affinity usually suffe...

Please sign up or login with your details

Forgot password? Click here to reset