# Multiway clustering of 3-order tensor via affinity matrix

arXiv: https://arxiv.org/abs/2303.07757 · HTML: https://mlsanity.com/paper/2303.07757/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 30 references that are in the map.
- First posted on arXiv 14 Mar 2023.

## Builds on (most cited first, 4 of 4)

- [A Tutorial on Principal Component Analysis](https://mlsanity.com/paper/1404.1100/) (2014)
- [Multiway clustering via tensor block models](https://mlsanity.com/paper/1906.03807/) (2019)
- [Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization](https://mlsanity.com/paper/1504.01777/) (2015)
- [Multi-Slice Clustering for 3-order Tensor Data](https://mlsanity.com/paper/2109.10803/) (2021)

## Built on by (most cited first, 1 of 1)

- [Parallel Computation of Multi-Slice Clustering of Third-Order Tensors](https://mlsanity.com/paper/2309.17383/) (2023)

## Abstract (arXiv)

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.