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  "Title": "Semi-Parametric Dimension Reduction Models Using Orthogonality\nConstrained Optimization",
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  "Description": "Utilize an orthogonality constrained optimization\nalgorithm of Wen & Yin (2013) <DOI:10.1007/s10107-012-0584-1>\nto solve a variety of dimension reduction problems in the\nsemiparametric framework, such as Ma & Zhu (2012)\n<DOI:10.1080/01621459.2011.646925>, Ma & Zhu (2013)\n<DOI:10.1214/12-AOS1072>, Sun, Zhu, Wang & Zeng (2019)\n<DOI:10.1093/biomet/asy064> and Zhou, Zhu & Zeng (2021)\n<DOI:10.1093/biomet/asaa087>. The package also implements some\nexisting dimension reduction methods such as hMave by Xia,\nZhang, & Xu (2010) <DOI:10.1198/jasa.2009.tm09372> and partial\nSAVE by Feng, Wen & Zhu (2013)\n<DOI:10.1080/01621459.2012.746065>. It also serves as a general\npurpose optimization solver for problems with orthogonality\nconstraints, i.e., in Stiefel manifold. Parallel computing for\napproximating the gradient is enabled through 'OpenMP'.",
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