Research map / Learning theory and algorithms / Clustering
Spectral clustering algorithms
Make spectral graph clustering efficient and analyze its behavior.
43 accepted papers at ICML, NeurIPS, ICLR, CVPR and AAAI (2016–2026) · an approach in Clustering, keyword cluster “correlation clustering · hierarchical · spectral clustering”
State History Tried Checklist Preprints Who Export
Where it stands
Not enough benchmark data Fewer than four papers report the same benchmark, so there is no record to follow.
11 papers in 2023–24 and 9 in 2025–26 (at ICML, NeurIPS, ICLR, CVPR and AAAI); its share of the topic shrank, from 7.9% to 4.4%.
How this is decided
A benchmark is tracked when at least four papers of this approach report their own method on the same dataset and metric in at least two different years. Its record is the best number reported up to 2024 compared with the best reported in 2025–26: still improving means at least 1% better, flat means at most 0.2% better with at least two papers from 2025–26 trying. Numbers on a different scale from the rest (a fraction among percentages) and far outliers are left out. Results come from different papers with different setups, so they are signals, not head-to-head comparisons. The share of papers is counted at ICML, NeurIPS, ICLR, CVPR and AAAI.
How it got here
Most cited paper of each year
- 2016 · The Constrained Laplacian Rank Algorithm for Graph-Based Clustering (AAAI 2016 · 854 citations)
- 2017 · Unsupervised Large Graph Embedding (AAAI 2017 · 152 citations)
- 2018 · Unified Spectral Clustering With Optimal Graph (AAAI 2018 · 114 citations)
- 2019 · Revisiting the Bethe-Hessian: Improved Community Detection in Sparse Heterogeneous Graphs (NeurIPS 2019 · 14 citations)
- 2020 · Spectral Clustering with Graph Neural Networks for Graph Pooling (ICML 2020 · 76 citations)
- 2021 · Theory of Spectral Method for Union of Subspaces-Based Random Geometry Graph (ICML 2021 · 0 citations)
- 2022 · GASP, a Generalized Framework for Agglomerative Clustering of Signed Graphs and Its Application to Instance Segmentation (CVPR 2022 · 19 citations)
- 2023 · Adaptive Graph Convolutional Subspace Clustering (CVPR 2023 · 39 citations)
- 2024 · Contrastive Learning is Spectral Clustering on Similarity Graph (ICLR 2024 · 2 citations)
- 2025 · Clustering by Mining Density Distributions and Splitting Manifold Structure (AAAI 2025 · 1 citation)
- 2026 · Simple Algorithms for Bad Triangle Transversals with Applications to Correlation Clustering (ICML 2026 · 0 citations)
Earliest papers here
- The Constrained Laplacian Rank Algorithm for Graph-Based Clustering (AAAI 2016 · 854 citations)
- Compressive Spectral Clustering (ICML 2016 · 57 citations)
- Scalable Sequential Spectral Clustering (AAAI 2016 · 26 citations)
What has been tried
38 papers here report 309 measured changes (a component added, removed or swapped, compared with a baseline): helped 70%, no clear effect 8%, hurt 18%, mixed 4%. Papers mostly publish changes that helped, so "helped" is over-represented.
Ablations in recent papers
| What was changed | Measured on | Result | Effect | Paper |
|---|---|---|---|---|
| replace Gaussian kernel with a Simple Sum mixture of Gaussian and Laplacian kernels | CIFAR-10 · accuracy | 88.11 ± 0.09 -> 89.82 ± 0.09; 90.60 ± 0.15 -> 91.72 ± 0.10 | Helped | Contrastive Learning is Spectral Clustering on Similarity Graph (ICLR 2024 · 2 citations) |
| Use density-based local pseudo-clusters rather than the whole dataset as the initial pseudo-cluster | mfea-fac, Kdd9, balance-scale, pengleukEW, optical_test, semeionEW, vote · ARI | 71.28 -> 86.28; 84.93 -> 96.53; 14.40 -> 24.60; 29.61 -> 35.85; 63.56 -> 84.08; 34.90 -> 52.62; 54.34 -> 57.10 | Helped | Clustering by Mining Density Distributions and Splitting Manifold Structure (AAAI 2025 · 1 citation) |
| Increase T in the Q phase | Synthetic graphs · clustering quality (NCut and ARI) | Helped | Pass-Efficient Algorithms for Graph Spectral Clustering (Student Abstract) (AAAI 2024 · 1 citation) | |
| Increase k above 2 | Synthetic and real-world clustering datasets · cluster purity | Helped | Biharmonic Distance of Graphs and its Higher-Order Variants: Theoretical Properties with Applications to Centrality and Clustering (ICML 2024 · 0 citations) | |
| Add a negative self-loop to the constraint graph | Temperature data · successful separation | 79.16% -> 79.16% | No clear effect | Signed Laplacians for Constrained Graph Clustering (ICML 2025) |
What reviewers will expect
Datasets and baselines named in the 6 papers of this approach from 2025–2026 that have a full-text summary. Leaving out the common ones is a frequent review question.
Datasets
- Pendigits · 2 of 6 papers
Recent preprints
Loading recent arXiv preprints…
Who publishes on it
Institutions on the most papers of this approach since 2023 (of 20 papers; from OpenAlex and the papers' affiliations).
- University of Edinburgh · 4 papers
- Massachusetts General Hospital · 2 papers
- University of Texas at Dallas · 2 papers
Use it
Download BibTeX of 34 key papersOpen the topic in the interactive map
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Related approaches
Same keyword cluster
- Clustering approximation algorithms (150 papers)
- Correlation clustering (102 papers)
- Subspace clustering (102 papers)
- Fairness-constrained clustering (19 papers)
- Incomplete multi-view clustering (125 papers)
Elsewhere in the topic
- Coresets and dynamic clustering (77 papers)
- k-means++ seeding analysis (76 papers)
- Fair clustering approximation (31 papers)
Benchmark numbers, ablations and baseline numbers are extracted by AI from each paper's full text and can be wrong; the paper is the authority. Data: results index of 2026-11-02, citation counts from OpenAlex (2026-10-09).