The DOI matches its Crossref record.
A deterministic annealing approach to clustering
Overview
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Citations
Cited by
A Survey of Quantization Methods for Efficient Neural Network Inference
Gholami, A., Kim, S., Dong, Z., Yao, Z., Mahoney, M. W., & Keutzer, K. (2022) · Low-Power Computer Vision · doi:10.1201/9781003162810-13 · Cited by 1,219
“This concept was extended and became practical in [53, 55, 67, 201] for real communication applications.”
Metadata
- Authors
- Rose, K., Gurewitz, E., & Fox, G.
- Venue
- Pattern Recognition Letters
- Publisher
- Elsevier BV
- Published
- 1990-09
- Volume
- 11
- Issue
- 9
- Pages
- 589-594
- ISSN
- 0167-8655 (ISSN-L)
- OpenAlex
- W2077096052
- Cited by
- 382
- References
- 0
- FWCI
- 3.17
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A deterministic annealing approach to clustering. https://app.cochat.ai/papers/10.1016/0167-8655(90)90010-y
- The paper
- Rose, K., Gurewitz, E., & Fox, G. (1990). A deterministic annealing approach to clustering. Pattern Recognition Letters. https://doi.org/10.1016/0167-8655(90)90010-y
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.