Spectral Clustering for Speech Separation

By Francis R. Bach, Michael I. Jordan. 2009

20 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Nino Antulov-Fantulin
2. Ivica Kopriva
3. Dijana Tolic

In Computer Vision and Pattern Recognition

1. Nino Antulov-Fantulin
2. Ivica Kopriva
3. Dijana Tolic

In Signal Processing

1. Nino Antulov-Fantulin
2. Ivica Kopriva
3. Dijana Tolic

Citations in the corpus

• A Nonlinear Orthogonal Non-Negative Matrix Factorization Approach to Subspace Clustering (2017, methodology): “Spectral clustering can be seen as a graph partition problem and solved by the eigenvalue decomposition of the graph Laplacian matrix [11, 12, 13, 14, 15].”