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Semidefinite embedding
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==References== * {{cite journal|author-last=Linial, London and Rabinovich | author-first=Nathan, Eran and Yuri|title=The geometry of graphs and some of its algorithmic applications|journal=Combinatorica|year=1995|volume=15| issue=2|pages=215β245| doi=10.1007/BF01200757| s2cid=5071936|url=https://www.researchgate.net/publication/228057833}} * {{cite conference|author-last= Weinberger, Sha and Saul|author-first=Kilian Q., Fei and Lawrence K.|title=Learning a kernel matrix for nonlinear dimensionality reduction|conference=Proceedings of the Twenty First International Conference on Machine Learning (ICML 2004). [[Banff, Alberta]], Canada|date=4 July 2004a|url=https://repository.upenn.edu/cis_papers/2/}} * {{cite conference|author-last=Weinberger and Saul|author-first=Kilian Q. and Lawrence K. | title=Unsupervised learning of image manifolds by semidefinite programming|volume=2|conference=2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition|date=27 June 2004b|url=https://repository.upenn.edu/cis_papers/1/}} * {{cite journal|author-last=Weinberger and Saul| author-first=Kilian Q. and Lawrence K.| title=Unsupervised learning of image manifolds by semidefinite programming|volume=70|journal=International Journal of Computer Vision|date=1 May 2006| pages=77β90|doi=10.1007/s11263-005-4939-z| s2cid=291166|url=http://bicmr.pku.edu.cn/~wenzw/bigdata/weinberger-saul-mvu-image-manifolds.pdf}} * {{cite journal|last=Lawrence|first=Neil D|title=A unifying probabilistic perspective for spectral dimensionality reduction: insights and new models|year=2012|pages=1612|volume=13|issue=May|journal=[[Journal of Machine Learning Research]]|url=http://www.jmlr.org/papers/v13/lawrence12a.html|bibcode=2010arXiv1010.4830L|arxiv=1010.4830}}
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