删除或更新信息,请邮件至freekaoyan#163.com(#换成@)

厦门大学数学科学学院导师教师师资介绍简介-黄文

本站小编 Free考研考试/2021-05-08


黄文
职称:教授
职务:
学历:博士
电子邮件:wen.huang@xmu.edu.cn
联系电话:
办 公 室:厦大海韵园物机楼604




教育经历:2014,美国佛罗里达州立大学,应用与计算数学,博士
2007,中国科学技术大学,信息与计算科学,学士
工作经历:
2018至今,厦门大学,数学科学学院,副教授
2016-2018,美国莱斯大学,计算与应用数学,法伊佛讲师博士后
2014-2016,比利时新鲁汶大学,ICTEAM,博士后研究员
2014,美国佛罗里达州立大学,科学计算,博士后研究员
2017-2018,厦门吉比特网络技术有限公司,数值策划


研究方向:
数值优化方法,主要包括流形上的优化算法设计分析、相关软件设计开发及其应用。应用包括图像处理,信号复原,机器学习,图论计算等。


近3年授课情况:
2020春,厦门大学,数值优化
2020春,厦门大学,微积分II
2019春,厦门大学,微积分II
2018春,美国莱斯大学,Pedagogy for RLAs
2018春,美国莱斯大学,Introduction to Engineering Computations


短课程:
2019,11月,复旦大学,大数据学院,流形上的优化
2019,12月,武汉大学(国家天元数学中部中心),流形上的优化


主持项目:
?国家自然科学基金(青年),流形上非光滑优化问题的算法研究及应用,主持


软件开发:
流形优化软件包(ROPTLIB)
该软件包提供流形优化算法用来求解不特定流形上的优化问题。用户提供目标函数,梯度或海森矩阵的作用以及与算法流形相关的参数,ROPTLIB即可返回优化后的结果及迭代信息。ROPTLIB由C++编写,同时提供了Matlab,Julia接口。具体信息见网页:
www.math.fsu.edu/~whuang2/Indices/index_ROPTLIB.html




部分论文:
· Chafik Samir*, Wen Huang*. "Coordinate Descent Optimization for One-to-One Correspondence with Applications to Supervised Classification of 3D Shapes", Applied Mathematics and Computation, accepted.


· Xinru Yuan, Wen Huang*, P.-A. Absil, K. A. Gallivan. "Computing the matrix geometric mean: Riemannian vs Euclidean conditioning, implementation techniques, and a Riemannian BFGS method", Numerical Linear Algebra with Applications, 27:5, 1-23, 2020.


· Sean Martin, Andrew M. Raim, Wen Huang, Kofi P. Adragni*. "ManifoldOptim: An R Interface to the ROPTLIB Library for Riemannian Manifold Optimization", Journal of Statistical Software, 93:1, pp. 1-32, 2020.


· Reinhard Heckel*, Wen Huang, Paul Hand, Vladislav Voroninski. "Deep Denoising: Rate-Optimal Recovery of Structured Signals with a Deep Prior", Information and Inference: A Journal of the IMA, 2020.


· Xinru Yuan, Wen Huang*, P.-A. Absil, Kyle A. Gallivan, "Averaging symmetric positive-definite matrices", In Springer Handbook on Variational methods for nonlinear geometric data and applications, pp. 555-575, 2020.


· Wen Huang*, Paul Hand. "Blind Deconvolution by a Steepest Descent Algorithm on a Quotient Manifold", SIAM Journal on Imaging Sciences, 11:4, pp. 2757-2785, 2018.


· Wen Huang*, P.-A. Absil, Kyle Gallivan, Paul Hand. "ROPTLIB: an object-oriented C++ library for optimization on Riemannian manifolds", ACM Transactions on Mathematical Software, 44:4, pp. 43:1-43:21, 2018.


· Somayeh Hosseini, Wen Huang*, Roholla Yousefpour. "Line Search Algorithms for Locally Lipschitz Functions on Riemannian Manifolds", SIAM Journal on Optimization, 28(1), pp. 596-619, 2018.


· Wen Huang*, P.-A. Absil, Kyle Gallivan. "A Riemannian BFGS Method without Differentiated Retraction for Nonconvex Optimization Problems", SIAM Journal on Optimization, 28:1, pp. 470-495, 2018.


· Wen Huang*, Kyle A. Gallivan, Xiangxiong Zhang. "Solving PhaseLift by low-rank Riemannian optimization methods for complex semidefinite constraints", SIAM Journal on Scientific Computing, 39:5, pp. B840-B859, 2017.


· Jim Wilgenbusch*, Wen Huang, Kyle A. Gallivan. "Visualizing Phylogenetic Tree Landscapes", BMC Bioinformatics, 18:85, DOI:10.1186/s12859-017-1479-1, 2017.


· Wen Huang*, P.-A. Absil, Kyle Gallivan. "Intrinsic Representation of Tangent Vectors and Vector Transport on Matrix Manifolds", Numerische Mathematik, 136:2, p.523-543, DOI:10.1007/s00211-016-0848-4, October, 2017.


· Wen Huang*, Guifang Zhou, Melissa Merchand, Jeremy Ash, Paul Van Dooren, Jeremy M. Brown, Kyle A. Gallivan, Jim Wilgenbush. "TreeScaper: visualizing and extracting phylogenetic signal from sets of trees", Molecular Biology and Evolution, 33(12):3314-3316 DOI:10.1093/molbev/msw196, 2016.


· Guifang Zhou, Wen Huang, Kyle Gallivan, Paul Van Dooren, P.-A. Absil*. "A Riemannian rank-adaptive method for low-rank optimization", Neurocomputing, 192, 72-80, June 2016.


· Wen Huang*, Kyle A. Gallivan, Anuj Srivastava, Pierre-Antoine Absil. "Riemannian Optimization for Registration of Curves in Elastic Shape Analysis", Journal of Mathematical Imaging and Vision, 54(3), 320-343, 2016.


· Wen Huang*, Kyle A. Gallivan, Pierre-Antoine Absil. "A Broyden Class of Quasi-Newton Methods for Riemannian Optimization", SIAM Journal on Optimization, 25:3, pp. 1660-1685, 2015.


· Wen Huang, Pierre-Antoine Absil*, Kyle A. Gallivan. "A Riemannian symmetric rank-one trust-region method", Mathematical Programming Series A, 150:2, pp. 179-216, 2015.


学生培养:
硕士
· ?Florentin Goyens(比利时新鲁汶大学,已毕业)
· 郭媛媛(厦门大学)
· 刘方玉(厦门大学)
· 秦婉璐(厦门大学)
博士(包括联合培养)
· 陈健恒(厦门大学)
· 司武涛(厦门大学)
· Tejas Natu(美国佛罗里达州立大学)
· 魏萌(美国佛罗里达州立大学)
· 张束光(美国佛罗里达州立大学)




相关话题/厦门大学 数学