Scaling Locally Linear Embedding
Summary: Ripple scales Locally Linear Embedding by incrementally updating edge weights via the Woodbury formula and computing kernel eigenvectors via an LU-based inverse power method. It preserves identical dimensionality reductions while delivering substantial speedups over vanilla LLE for large-scale data. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Yasuhiro Fujiwara (Nippon Telegraph and Telephone Corporation; Osaka University)
- 2. Naoki Marumo (Nippon Telegraph and Telephone Corporation)
- 3. Mathieu Blondel (Nippon Telegraph and Telephone Corporation)
- 4. Koh Takeuchi (Nippon Telegraph and Telephone Corporation)
- 5. Hideaki Kim (Nippon Telegraph and Telephone Corporation)
- 6. Tomoharu Iwata (Nippon Telegraph and Telephone Corporation)
- 7. Naonori Ueda (Nippon Telegraph and Telephone Corporation)
BibTeX Citation
@inproceedings{fujiwara_sigmod17,
title = {{Scaling Locally Linear Embedding}},
author = {Fujiwara, Yasuhiro and Marumo, Naoki and Blondel, Mathieu and Takeuchi, Koh and Kim, Hideaki and Iwata, Tomoharu and Ueda, Naonori},
series = {{SIGMOD} '17},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3035918.3064021},
url = {https://dl.acm.org/doi/10.1145/3035918.3064021},
year = {2017}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 41 | Fast Subsequence Matching in Time-Series Databases | 1994 | SIGMOD | 0.00046675394 |
| 190 | Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases | 2001 | SIGMOD | 0.00026105472 |
| 610 | Efficiently Supporting Ad Hoc Queries in Large Datasets of Time Sequences | 1997 | SIGMOD | 0.00015783259 |
| 1,280 | Indexing Spatio-Temporal Trajectories with Chebyshev Polynomials | 2004 | SIGMOD | 0.00011354776 |
| 1,414 | Fast and Exact Top-k Search for Random Walk with Restart | 2012 | VLDB | 0.00010848387 |
| 1,722 | Indexable PLA for Efficient Similarity Search | 2007 | VLDB | 9.9227051e-05 |
| 2,839 | SCAN++: Efficient Algorithm for Finding Clusters, Hubs and Outliers on Large-scale Graphs | 2015 | VLDB | 8.066541e-05 |
| 6,486 | Madeus: Database Live Migration Middleware under Heavy Workloads for Cloud Environment | 2015 | SIGMOD | 5.8651891e-05 |
| 12,153 | Scaling Manifold Ranking Based Image Retrieval | 2015 | VLDB | 5.093636e-05 |
| 13,538 | Fast Algorithm for the Lasso based L1-Graph Construction | 2017 | VLDB | - |
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