{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T19:51:43Z","timestamp":1760385103322,"version":"3.28.0"},"reference-count":34,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,7]]},"DOI":"10.1109\/ijcnn.2010.5596571","type":"proceedings-article","created":{"date-parts":[[2010,10,19]],"date-time":"2010-10-19T14:58:15Z","timestamp":1287500295000},"page":"1-8","source":"Crossref","is-referenced-by-count":2,"title":["Projection Vector Machine: One-stage learning algorithm from high-dimension small-sample data"],"prefix":"10.1109","author":[{"given":"Wanyu","family":"Deng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qinghua","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiguo","family":"Lian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lin","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","first-page":"211","article-title":"Sparse Bayesian Learning and the Relevance Vector Machine","volume":"1","author":"michael tipping","year":"2001","journal-title":"Journal of Machine Learning Research"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-2440-0"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1023\/B:MACH.0000008083.47006.86"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/72.88168"},{"article-title":"Neural Networks: A Comprehensive Foundation","year":"1999","author":"haykin","key":"ref34"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.79"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2009.05.005"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TITB.2008.2007421"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.184"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/17.6.566"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1126\/science.290.5500.2323"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1126\/science.1127647"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1037\/h0071325"},{"journal-title":"Dimensionality Reduction AComparative Review","year":"0","author":"van","key":"ref18"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-1809.1936.tb02137.x"},{"journal-title":"UCI repository of machine learning databases","year":"1999","author":"blake","key":"ref28"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2003.809401"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1162\/089976698300017467"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557072"},{"journal-title":"ELM Source Codes","year":"0","key":"ref6"},{"key":"ref29","first-page":"623","article-title":"Scalable Collaborative Filtering Approaches for Large Recommender Systems","volume":"10","author":"takacs","year":"2009","journal-title":"Journal of Machine Learning Research"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/72.329697"},{"journal-title":"Matrix Computations","year":"1989","author":"golub","key":"ref8"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICARCV.2006.345467"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557150"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557093"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2009.123"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2005.12.126"},{"key":"ref22","first-page":"7426","article-title":"Hessian eigenmaps: New locally linear embedding techniques for high-dimensional data","volume":"102","author":"donoho","year":"2005","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1137\/S1064827502419154"},{"key":"ref24","first-page":"585","article-title":"Laplacian Eigenmaps and spectral techniques for embedding and clustering","volume":"14","author":"belkin","year":"2002","journal-title":"Advances in neural information processing systems"},{"key":"ref23","first-page":"841","article-title":"Automatic alignment of hidden representations","volume":"15","author":"teh","year":"2002","journal-title":"Advances in neural information processing systems"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"2319","DOI":"10.1126\/science.290.5500.2319","article-title":"A global geometric framework for nonlinear dimensionality reduction","volume":"290","author":"tenenbaum","year":"2000","journal-title":"Science"},{"key":"ref25","first-page":"682","article-title":"Mapping a manifold of perceptual observations","volume":"10","author":"tenenbaum","year":"1998","journal-title":"Advances in neural information processing systems"}],"event":{"name":"2010 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2010,7,18]]},"location":"Barcelona, Spain","end":{"date-parts":[[2010,7,23]]}},"container-title":["The 2010 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx5\/5581822\/5595732\/05596571.pdf?arnumber=5596571","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,19]],"date-time":"2017-06-19T11:15:48Z","timestamp":1497870948000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/5596571\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,7]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/ijcnn.2010.5596571","relation":{},"subject":[],"published":{"date-parts":[[2010,7]]}}}