Randomized SVD Approximations for Spectral Co-Clustering of Word-Document Matrices

arXiv:2609.19243 · cs.LG, cs.AI · Submitted 2026-09-16 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-09-16

Updated: 2026-09-16

Comments: Accepted to 2026 IEEE International Conference on Machine Learning and Applications (ICMLA)

Code: https://github.com/mazdarani/randomized-spectral-coclustering

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Clustering — 82× in this paper · explained in 2 episodes
• Accuracy — 15× in this paper · explained in 1 episode
• Sparsity — 6× in this paper · explained in 4 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Spectral clustering — 3× in this paper · explained in 2 episodes
• Adjacency Matrix — 2× in this paper · explained in 1 episode
• Singular Value Decomposition (SVD) — 2× in this paper · explained in 2 episodes
• Spectral Co-Clustering with Partial SVD — 2× in this paper
• Graph Construction — 1× in this paper · explained in 3 episodes
• Heterogeneous Graph — 1× in this paper · explained in 2 episodes
• Implicitly Restarted Lanczos Bidiagonalization Algorithm — 1× in this paper
• Redundancy — 1× in this paper · explained in 2 episodes
• Spectral Co-Clustering with Random Projection — 1× in this paper

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