The DOI matches its Crossref record.
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
High-Speed Tracking with Kernelized Correlation Filters
Henriques, J. F., Caseiro, R., Martins, P., & Batista, J. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2345390 · Cited by 5,753
Artificial intelligence for fault diagnosis of rotating machinery: A review
Liu, R., Yang, B., Zio, E., & Chen, X. (2018) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2018.02.016 · Cited by 2,188
Gong, D., Liu, L., Le, V., Saha, B., Mansour, M. R., Venkatesh, S., & Van Den Hengel, A. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00179 · Cited by 1,930
Kernel-based methods for hyperspectral image classification
Camps-Valls, G., & Bruzzone, L. (2005) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2005.846154 · Cited by 1,453
Searching molecular structure databases with tandem mass spectra using CSI:FingerID
Dührkop, K., Shen, H., Meusel, M., Rousu, J., & Böcker, S. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1509788112 · Cited by 1,190
Metadata
- Venue
- IEEE Transactions on Neural Networks
- Published
- 2005-05
- Volume
- 16
- Issue
- 3
- Pages
- 781-781
- ISSN
- 1045-9227 (ISSN-L)
- OpenAlex
- W3195149063
- Cited by
- 2,225
- References
- 0
- FWCI
- 61.84
- 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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. https://app.cochat.ai/papers/10.1109/tnn.2005.848998
- The paper
- Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. (2005). IEEE Transactions on Neural Networks. https://doi.org/10.1109/tnn.2005.848998
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.