Publications
- Preprinted papers
- Wen Huang, Zilin Yang, Qinglin Tang, "A preconditioned Riemannian conjugate gradient method to compute ground states of Spin-1 Bose-Einstein condensates".
- Zhenwei Huang, Wen Huang*, Pratik Jawanpuria, Bamdev Mishra, "Riemannian Federated Learning via Averaging Gradient Stream".
- Chunming Tang, Shajie Xing, Wen Huang*, Jinbao Jian, "A restricted memory quasi-Newton bundle method for nonsmooth optimization on Riemannian manifolds".
- Zhanwang Deng, Yuqiu Su, Wen Huang*, "SLRQA: A Sparse Low-Rank Quaternion Model for Color Image Processing with Convergence Analysis".
- Wen Huang*, Wutao Si, "A Riemannian Proximal Newton-CG Method".
- Zhenwei Huang, Wen Huang*, Pratik Jawanpuria, Bamdev Mishra, "Federated Learning on Riemannian Manifolds with Differential Privacy".
- Jian-Feng Cai, Wen Huang, Haifeng Wang, Ke Wei*, "Tensor Completion via Tensor Train Based Low-Rank Quotient Geometry under a Preconditioned Metric".
- Shuyu Dong*, Bin Gao, Wen Huang, Kyle A. Gallivan, "On the analysis of optimization with fixed-rank matrices: a quotient geometric view".
- Papers in Journals
- Shixin Zheng, Wen Huang, Bart Vandereycken, Xiangxiong Zhang, "Riemannian optimization using three different metrics for Hermitian PSD fixed-rank constraints: an extended version", Accepted in Computational Optimization and Applications.
- Zhenwei Huang, Wen Huang*, "An increasing rank Riemannian method for generalized Lyapunov equations", Journal of Scientific Computing, 102:74, DOI:10.1007/s10915-025-02807-2, 2025.
- Wen Huang*, Meng Wei, Kyle A. Gallivan, Paul Van Dooren, "A Riemannian Optimization Approach to Clustering Problems", Journal of Scientific Computing, 103:8, DOI:10.1007/s10915-025-02806-3, 2025.
- Jianheng Chen, Wen Huang*, "Rank-one approximation of a higher-order tensor by a Riemannian trust-region method", Computational Optimization and Applications, 90, 515-556, 2025.
- Chenyu Zhang, Rufeng Xiao, Wen Huang, Rujun Jiang*, "Riemannian Trust Region Methods for SC1 Minimization", Journal of Scientific Computing, 101:32, DOI:10.1007/s10915-024-02664-5, 2024.
- Zeyu Zhou, Wen Huang, Wei Jiang, and Zhen Zhang*, "An operator-splitting optimization approach for phase-field simulation of equilibrium shapes of crystals", SIAM Journal on Scientific Computing, 46:3, B331-B353, 2024.
- Jianheng Chen, Wen Huang*, "An iterative algorithm for low-rank tensor completion problem with sparse noise and missing values", Numerical Linear Algebra with Applications, 31:3, e2544, 2024.
- Wutao Si, P.-A. Absil, Wen Huang*, Rujun Jiang, Simon Vary, "A Riemannian Proximal Newton Method", SIAM Journal on Optimization, 34:1, pp. 654-681, 2024.
- Qiangwei Peng, Wen Huang*, "An Image Inpainting Algorithm using Exemplar Matching and Low-Rank Sparse Prior", Inverse Problems, 40:1, 015002, 2024.
- Wen Huang*, Ke Wei*, "An Inexact Riemannian Proximal Gradient Method", Computational Optimization and Applications, 85, 1-32, 2023.
- Yuetian Luo, Wen Huang, Xudong Li, Anru R. Zhang*. "Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence", Operations Research, doi:10.1287/opre.2023.2445, 2023.
- Wen Huang*, Kyle A. Gallivan. "A limited-memory Riemannian symmetric rank-one trust-region method with a Restart Strategy", Journal of Scientific Computing, 93:1, doi:10.1007/s10915-022-01962-0, 2022.
- Wen Huang*, Ke Wei*, "An Extension of Fast Iterative Shrinkage-thresholding to Riemannian Optimization for Sparse Principal Component Analysis", Numerical Linear Algebra with Applications, 29(1), e2409, 2022.
- Shuailing Feng, Wen Huang, Lele Song, Shihui Ying*, Tieyong Zeng, "Proximal gradient method for nonconvex and nonsmooth optimization on Hadamard manifolds", Optimization Letters, 16, 2277-2297, 2022.
- Melissa Marchand, Kyle Gallivan, Wen Huang, Paul Van Dooren*, "Analysis of the Neighborhood Pattern Similarity Measure for the Role Extraction Problem", SIAM Journal on Mathematics of Data Science, 3:2, pp. 736-757, 2021.
- Wen Huang*, Ke Wei*. "Riemannian Proximal Gradient Methods", Mathematical Programming, doi:10.1007/s10107-021-01632-3, 2021.
- Wen Huang*, Paul Hand, Reinhard Heckel, Vladislav Voroninski. "A Provably Convergent Scheme for Compressive Sensing under Random Generative Priors", Journal of Fourier Analysis and Applications, 27, doi:10.1007/s00041-021-09830-5, 2021.
- Chafik Samir*, Wen Huang. "Coordinate Descent Optimization for One-to-One Correspondence with Applications to Supervised Classification of 3D Shapes", Applied Mathematics and Computation, 388, 125539, 2021.
- 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. "Rate-optimal denoising with deep neural networks", Information and Inference: A Journal of the IMA, 10(4), 1251-1285, 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.
- Book Chapters
- Peer reviewed conference papers
- Jiali Wang, Wen Huang, Rujun Jiang*, Xudong Li, Alex L. Wang. "Solving Stackelberg Prediction Game with Least Squares Loss Via Spherically Constrained Least Squares Reformulation", In Proceeding of International Conference on Machine Learning 2022 (ICML), Outstanding paper award, 2022.
- Wen Huang*. "Heuristics for optimization with nonnegativity constraints using ideas from Riemannian optimization", In Proceeding of The 24st International Symposium on Mathematical Theory of Networks and Systems, IFAC-PapersOnLine, 54:9, 552-557, 2021.
- Meng Wei, Wen Huang*, Kyle A. Gallivan, Paul Van Dooren. "Community Detection by a Riemannian Projected Proximal Gradient Method", In Proceeding of The 24st International Symposium on Mathematical Theory of Networks and Systems, IFAC-PapersOnLine, 54:9, 544-551, 2021.
- Wen Huang*, Kyle A. Gallivan. "A limited-memory Riemannian symmetric rank-one trust-region method with an efficient algorithm for its subproblem", In Proceeding of The 24st International Symposium on Mathematical Theory of Networks and Systems, IFAC-PapersOnLine, 54:9, 572-577, 2021.
- Melissa Marchand*, Wen Huang, Arnaud Browet, Paul Van Dooren, Kyle A. Gallivan. "A Riemannian Optimization Approach for Role Model Extraction", In Proceeding of The 22st International Symposium on Mathematical Theory of Networks and Systems (MTNS 2016).
- Wen Huang*, Kyle A. Gallivan, Xiangxiong Zhang. "Solving PhaseLift by low-rank Riemannian optimization methods", Procedia Computer Science, 80:1125-1134, 2016.
- Xinru Yuan, Wen Huang*, P.-A. Absil, K. A. Gallivan. "A Riemannian Limited-memory BFGS Algorithm for Computing the Matrix Geometric Mean", Procedia Computer Science, 80:2147-2157, 2016.
- Wen Huang*, P.-A. Absil, Kyle Gallivan. "A Riemannian BFGS Method for Nonconvex Optimization Problems", Lecture Notes in Computational Science and Engineering, DOI:10.1007/978-3-319-39929-4_60, 2016.
- Yaqing You, Wen Huang*, Kyle A. Gallivan, Pierre-Antoine Absil. "A Riemannian Approach for Computing Geodesics in Elastic Shape Analysis", In Proceeding of the 3rd IEEE Global Conference on Signal and Information Processing (GlobalSIP2015).
- Wen Huang*, Yaqing You, Kyle A. Gallivan, Pierre-Antoine Absil. "Karcher Mean in Elastic Shape Analysis", In Proceeding of the 1st International Workshop on DIFFerential Geometry in Computer Vision for Analysis of Shapes, Images and Trajectories (DIFF-CV 2015).
- Matthieu Genicot*, Wen Huang, Nickolay T. Trendafilov. "Weakly Correlated Sparse Components with Nearly Orthonormal Loadings", In Proceeding of Geometric Science of Information (GSI 2015).
- Guifang Zhou, Wen Huang*, Kyle A. Gallivan, Paul Van Dooren, Pierre-Antoine Absil. "Rank-Constrained Optimization: A Riemannian Manifold Approach", In Proceeding of European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2015).
- Wen Huang*, Kyle A. Gallivan, Anuj Srivastava, Pierre-Antoine Absil. "Riemannian Optimization for Elastic Shape Analysis", In Proceeding of The 21st International Symposium on Mathematical Theory of Networks and Systems (MTNS 2014).
- Thesis and conference papers
- Melissa Marchand*, Wen Huang, Kyle Gallivan, Bradley Marchand. "Multi-input multi-output waveform optimization for synthetic aperture sonar", In Proceeding of the International Society for Optics and Photonics, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI, 98231X (May 3, 2016), doi:10.1117/12.2229054.
- Wen Huang, "Optimization Algorithms on Riemannian Manifolds with Applications", Ph.D Thesis, Department of Mathematics, Florida State University, 2014.
- Short Courses and Seminars
- Tianyuan Mathematical Center, Southwest Center, Sichuan University, Chengdu, China, TBA
Title: Riemannian Optimization Series 3: Second Order Optimization Methods and Quotient Manifolds, Course Materials
- Tianyuan Mathematical Center, Southwest Center, Sichuan University, Chengdu, China, TBA
Title: Riemannian Optimization Series 2: Embedded Submanifolds and First Order Optimization Methods, Course Materials
- Tianyuan Mathematical Center, Southwest Center, Sichuan University, Chengdu, China, November 1-6, 2021
Title: Riemannian Optimization Series 1: Basics on Optimization, Course Materials
- Department of Automation, Tsinghua University, Online seminar, China, January, 2021
Title: Optimization on Riemannian manifolds.
- School of Mathematical Sciences, Nanjing Normal University, Nanjing, China, January, 2021
Title: Optimization on Riemannian manifolds.
- College of Mathematics and Information Science, Guangxi University, Nanning, China, December, 2020
Title: Optimization on Riemannian manifolds.
- Tianyuan Mathematical Center, Central Center, Wuhan University, Wuhan, China, November-December, 2019
Title: Optimization on Manifolds, Course Materials
- The School of Data Science, Fudan University, Shanghai, China, November, 2019
Title: Optimization on Manifolds, Course Materials
- Talks
- Huazhong University of Science and Technology, Wuhan, China, October, 2024
Title: Riemannian Optimization and a Riemannian Proximal Newton Method (online), Slides
- 2024广西数学优化前沿研讨会 (2024Guangxi Mathmatical Optimization workshop), China, November, 2024
Title: A Riemannian Proximal Newton-CG Method, Slides
- School of Data Science, Fudan University, Shanghai, China, November, 2024
Title: Riemannian Optimization and a Riemannian Proximal Newton-CG Method, Slides
- Learning and Optimization over Riemannian Manifolds, Fudan University, Shanghai, China, November, 2024
Title: Riemannian Federated Learning via Averaging Gradient Stream, Slides
- 优化理论与方法研讨会，Great Bay University, Dalian, China, November, 2024
Title: Federated Learning on Riemannian Manifolds with Differential Privacy, Slides
- Dongguan University of Technology, Dongguan, China, October, 2024
Title: Riemannian Optimization and a Riemannian Proximal Newton-CG Method (online), Slides
- 2024年中国运筹学会第十七届年会，17th Annual Conference of Operations Research Society of China, China, October, 2024
Title: A Riemannian Proximal Newton-CG Method, Slides
- School of Mathematical Sciences, Dalina University of Technology, Dalian, China, Setember, 2024
Title: Federated Learning on Riemannian Manifolds with Differential Privacy, Slides
- Matrix Optimization, Hunan University, Changsha, China, Setember, 2024
Title: A Riemannian Proximal Newton-CG Method, Slides
- Matrix Optimization, Hunan University, Changsha, China, Setember, 2024
Title: A Riemannian Proximal Newton-CG Method, Slides
- School of Mathematics and Statistics, Wuhan University, Wuhan, China, January, 2024
Title: Riemannian Optimization: A Proximal Newton Method, Slides
- 第一届算法软件与应用研讨会（ASA2023), Tianjin, China, November, 2023
Title: Riemannian Optimization: A Proximal Newton Method, Slides
- 第二届运筹与优化前沿学术会议, Shenzhen University, Shenzhen, China, November, 2023
Title: An Increasing Rank Riemannian Method for Generalized Lyapunov Equations, Slides
- Department of Mathematics, Southern University of Science and Technology, Shenzhen, China, August, 2023
Title: Riemannian Optimization with its Applications to Clustering Problems, Slides
- School of Mathematical Sciences, Shenzhen University, Shenzhen, China, August, 2023
Title: Riemannian Optimization with its Applications to Clustering Problems, Slides
- School of Mathematics and Physics, Guanxi Minzu University, Nanning, China, August, 2023
Title: Riemannian Optimization with its Applications to Clustering Problems, Slides
- School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, China, August, 2023
Title: Riemannian Optimization with its Applications to Clustering Problems, Slides
- School of Mathematics, Renmin University of China, Beijing, China, July, 2023
Title: Riemannian proximal gradient methods and variants, Slides
- Academy of Mathematics and Systems Science, Chinese Academy of Science, Beijing, China, July, 2023
Title: Riemannian proximal gradient methods and variants, Slides
- School of Mathematical Sciences, Beijing University, Beijing, China, July, 2023
Title: Riemannian proximal gradient methods and variants, Slides
- SIAM Conference on Optimization, Seattle, Washington, U.S., June, 2023
Title: A Riemannian Proximal Newton Method, Slides (Given by Wutao Si)
- Workshop on Optimization and Applications, Fuzhou, Fujian, March, 2023
Title: A Riemannian Proximal Newton Method, Slides
- 中国运筹学会第十六届全国数学优化学术会议暨数学优化分会代表大会, Changsha, Hunan, April, 2023
Title: An iterative algorithm for low-rank tensor completion problem with sparse noise and missing values, Slides
- Workshop on Optimization and Applications, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, November, 2022
Title: A limited-memory Riemannian symmetric rank-one trust-region method with a restart strategy, Slides
- Joint Mathematics Seminar of Xiamen University and Xiamen University Malaysia, July, 2022
Title: A Riemannian Optimization Approach to Clustering Problems
- Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, June, 2022
Title: Riemannian Optimization with its Application to Clustering Problems
- 2021最优化前沿青年研讨会 (Online), Southern University of Science and Technology, December, 2021
Title: An Inexact Riemannian Proximal Gradient Method
- 2021年第七届科学与工程计算青年研讨会 (SCF-YSSEC Online), November, 2021
Title: A Riemannian Optimization Approach to Clustering Problems
- 人工智能中的数学方法与优化学术刑只, Hangzhou Dianzi University (Online), November, 2021
Title: An Inexact Riemannian Proximal Gradient Method, Slides
- Communication and Cooperation on Froniter Optimization and Applications, Xiamen University (Online), August, 2021
Title: Riemannian Optimization and Its Application to Clustering Problems
- Huawei Technologies Co. LTD., Online, July, 2021
Title: An Introduction to Riemannian Optimization and its Applications
- Workshop on Operation Research and Optimization, Fudan University, July, 2021
Title: A Riemannian Optimization Approach to Clustering Problems
- School of Sciences, Shanghai University, July, 2021
Title: Riemannian Optimization with its Application to Community Detection
- School of Science, Nanjing University of Science and Technology, online, June, 2021
Title: Riemannian Optimization with its Application to Community Detection
- Frontier Forum of Computational Mathematics (厦门大学计算数学科学前沿论坛), Xiamen University, Xiamen, May, 2021
Title: Riemannian Optimization: Proximal Gradient Methods, Slides
- 2020南京地区最优化理论与算法青年论坛, Nanjing University, Nanjing, January, 2021
Title: Riemannian quasi-Newton methods, implementation techniques, and applications, Slides
- School of Mathematical Sciences, Xiamen University, Xiamen, China, December, 2020
Title: Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence, Slides
- School of Mathematics and Information Science, Guangxi University, Nanning, China, December, 2020
Title: Riemannian quasi-Newton methods, implementation techniques, and applications, Slides
- 刘应明院士诞辰80周年纪念系列学术活动 “数值计算方法与理论前沿研讨会2020”, Sichuan University, Sichuan, China, November, 2020
Title: Geometric mean of symmetric positive definite matrices, Slides
- Symposium on the Frontiers of Mathematical Optimization Research, Guangxi University, Guangxi (online), China, July, 2020
Title: Riemannian Proximal Gradient Methoods, Slides
- School of Data Science, Fudan University, Shanghai, China, June, 2020
Title: Riemannian quasi-Newton methods, implementation techniques, and applications, Slides
- Department of Mathematics, Sichuan University, Chengdu, China, January, 2020
Title: Riemannian Proximal Gradient Methods, Slides
- Department of Mathematics, Sourthern University of Science and Technology of China, Shenzhen, China, December, 2019
Title: Riemannian Proximal Gradient Methods, Slides
- 第二届福建省计算数学学术研讨会, Fuzhou, China, December, 2019
Title: Riemannian Optimization with its Application to Blind Deconvolution Problem, Slides
- 13th National Congress of the Chinese Mathematical Society (中国数学会学术年会), Foshan, China, November, 2019
Title: Riemannian Proximal Gradient Methods, Slides
- Department of Mathematics, Nanjing University, Nanjing, China, October, 2019
Title: Riemannian Proximal Gradient Methods, Slides
- Department of Mathematics, Nanjing Normal University, Nanjing, China, October, 2019
Title: Riemannian Proximal Gradient Methods, Slides
- Department of Mathematics, Nanjing University, Nanjing, China, October, 2019
Title: Riemannian Optimization with its Application to Averaging Positive Definite Matrices, Slides
- Academy of Mathematics and Systems Science, Chinese Academy of Science, Beijing, China, September, 2019
Title: Riemannian Proximal Gradient Methods, Slides
- Academy of Mathematics and Systems Science, Chinese Academy of Science, Beijing, China, September, 2019
Title: Riemannian Optimization and its Application to Elastic Shape Analysis, Slides
- SIAM Conference on Applied Algebraic Geometry, Bern, Switzerland, July, 2019
Title: A Riemannian Proximal Gradient Descent Method
- 中国运筹学会第十二届全国数学优化学术会议暨数学优化分会代表大会, Nanjing, China, April, 2019
Title: A Technique in Implementations of Riemannian quasi-Newton Methods, Slides
- The 12th International Conference on Numerical Optimization and Numerical Linear Algebra, Shangrao, China, April, 2019
Title: Riemannian Optimization for Computing Low-rank Solutions of Lyapunov Equations with a New Preconditioner, Slides
- Joint meeting of Wuhan University and Xiamen University, Wuhan, China, December, 2018
Title: Riemannian Optimization with its Application to Averaging Positive Definite Matrices, Slides
- Xiamen University Malaysia, Malaysia, November, 2018
Title: Riemannian Optimization with its Application to Averaging Positive Definite Matrices, Slides
- Joint meeting of Jilin University and Xiamen University, Xiamen, China, October, 2018
Title: Riemannian Optimization and Averaging Symmetric Positive Definite Matrices, Slides
- Beijing International Center for Mathematical Research, Beijing University, Beijing, China, October, 2018
Title: Riemannian Optimization and Averaging Symmetric Positive Definite Matrices, Slides
- Yau Mathematical Sciences Center, Tsinghua University, Beijing, China, October, 2018
Title: Riemannian Optimization and Averaging Symmetric Positive Definite Matrices, Slides
- SIAM Conference on Applied Linear Algebra, Hong Kong, China, May, 2018
Title: Riemannian Optimization and the Computation of the Divergences and the Karcher Mean of Symmetric Positive Definite Matrices, Slides
- SIAM Conference on Applied Linear Algebra, Hong Kong, China, May, 2018
Title: Blind Deconvolution by Optimizing Over a Quotient Manifold, Slides
- Xiamen University, Department of Mathematics, Xiamen, China, April, 2018
Title: Riemannian Optimization with its Application to Blind Deconvolution Problem, Slides
- East China Normal University, Department of Mathematics, Shanghai, China, April, 2018
Title: Riemannian Optimization with its Application to Blind Deconvolution Problem, Slides
- Chinese University of Hong Kong, School of Science and Engineering, Hong Kong, China, April, 2018
Title: Riemannian Optimization with its Application to Blind Deconvolution Problem, Slides
- Young Talents Workshop, Zhejiang University, School of Mathematical Sciences, Hangzhou, China, Mar. 2018
Title: Blind deconvolution by optimizing over a quotient manifold, Slides
- Rice University, Department of Computational and Appiled Mathematics, Houston, USA, Jan. 2018
Title: Blind deconvolution by optimizing over a quotient manifold, Slides
- Fudan Science and Innovation Forum, Fudan University, Shanghai, China, Dec. 2017
Title: Blind deconvolution by optimizing over a quotient manifold, Slides
- University of Geneva, Mathematics department, Geneva, Swiss, Dec. 2017
Title: Blind deconvolution by optimizing over a quotient manifold, Slides
- Purdue University, Center for Computational and Applied Mathematics, West Lafayette, USA, Nov. 13, 2017
Title: Blind deconvolution by optimizing over a quotient manifold, Slides
- International Linear Algebra Seciety, Ames, USA, July 24-28, 2017
Title: Intrinsic Representation of Tangent Vectors and Vector Transport on Matrix Manifolds: A Technique in Implementations of Riemannian Optimization Algorithms, Slides
- SIAM Conference on Optimization, Vancouver, Canada, May 22-25, 2017
Title: Introduction to Riemannian BFGS methods, Slides
- International Conference on Computational Science, San Diego, California, USA, June, 2016
Title: Solving PhaseLift by low-rank Riemannian optimization methods, Slides
- International Conference on Computational Science, San Diego, California, USA, June, 2016
Title: A Riemannian Limited-memory BFGS Algorithm for Computing the Matrix Geometric Mean, Slides (Given by Xinru Yuan)
- The Renmin University of China, Institute for Mathematical Sciences, April, 2016
Title: Riemannian Optimization and its Application to Phase Retrieval Problem, Slides
- Shanghai University, Department of Mathematics, April, 2016
Title: Riemannian BFGS methods and its Applications, Slides
- The Chinese University of Hong Kong (Shenzhen), The School of Science and Engineering, March, 2016
Title: Riemannian Optimization and its Application to Computations on Symmetric Positive Definite Matrices, Slides
- The Global Scientist Forum, the Southern University of Science and Technology of China, Department of Mathematics, March, 2016
Title: Riemannian Optimization and its Application to Elastic Shape Analysis, Slides
- Zhejiang University of Technology, Department of Mathematics, January, 2016
Nanjing University, Department of Mathematics, January, 2016
Academy of Mathematics and Systems Science, Chinese Academy of Science, December, 2015
Huazhong University of Science and Technology, Center for Mathematical Science, December, 2015
Title: An Introduction to Riemannian Optimization and its Applications, Slides
- The 3rd IEEE Global Conference on Signal and Information Processing (GlobalSIP2015), Orlando, December, 2015
Title: A Riemannian Approach for Computing Geodesics in Elastic Shape Analysis Slides (Given by Yaqing You)
- Phyleaus Laboratory Meeting, Biological Sciences Department, Louisiana State University, October, 2015
Title: Network Analysis of Phylogenetic Data Slides (Given by Guifang Zhou)
- Geometric Science of Information (GSI2015), Paris-Saclay, France, October, 2015
Title: Weakly Correlated Sparse Components with Nearly Orthonormal Loadings Slides (Given by Matthieu Genicot)
- European Conference on Numerical Mathematics and Advanced Applications (ENUMATH2015), Ankara, Turkey, September, 2015
Title: A Riemannian BFGS Method for Nonconvex Optimization Problems Slides
- Seminar in Unversity of Namur, Namur, Belgium, May, 2015
Topic: Riemannian Optimization with an Application in Elastic Shape Analysis Slides
- Research Group on Riemannian And NonSmooth Optimization (RANSO) meeting, Liege, Belgium, May, 2015
Topic: A C++ Riemannian Optimization Package Slides
- The 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN2015), Bruges, Belgium, April, 2015
Topic: Rank-constrained Optimization: A Riemannian Manifold Approach Slides
- The 34th Benelux Meeting on Systems and Control, Lommel, Belgium, March, 2015
Topic: Solving PhaseLift by low-rank Riemannian optimization methods for complex semidefinite constraints Slides
- iEvoBio meeting, Raleigh, NC, June, 2014
Topic: TreeScaper: Software to visualize and understand tree landscapes Slides
- Evolution meeting, Raleigh, NC, June, 2014
Topic: Using networks of topologies and bipartitions to explore, quantify, and summarize phylogenetic tree space Slides (Given by Jeremy M. Brown )
- iEvoBio meeting, Portland, OR, June, 2010
Topic: The Shape and Dimensionality of Phylogenetic Tree-Space Based on Mitochondrial Genomes (Given by James C. Wilgenbusch )
- Posters and Abstract
- European Conference on Numerical Mathematics and Advanced Applications (ENUMATH2015), Ankara, Turkey, September, 2015
Title: A Riemannian BFGS Method for Nonconvex Optimization Problems Abstract
- Workshop: Differential Geometry in Computer Vision for Analysis of Shapes, Images and Trajectories, Swansea, the United Kingdom, September, 2015
Title: Karcher Mean in Elastic Shape Analysis Poster
- Workshop: Low-rank Optimization and Applications, Bonn, June, 2015
Title: A Riemannian Optimization Technique for Rank Inequality Constraints Poster
- Dynamical Systems, Control, and Optimization (DYSCO) study day, UGent, November, 2014
Title: A Riemannian Optimization Technique for Rank Inequality Constraints Poster
- Evolution Meetings, Raleigh, NC, June, 2014
Title: Community detection on networks of topologies and bipartitions identifies conflicting phylogenetic signal (Given by Jeremy Ash ) Poster
- 2012 Workshop on Advances in Computational Mathematics and Engineering, Tallahassee, FL, September, 2012
Title: Evaluation and Application of Nonlinear Dimensionality Reduction Methods for Phylogenetic Inference. Poster
- Evolution Meetings, Ottowa, Canada, July, 2012
Title: Visualizing the consequences of model mis-specification in phylogenetic tree landscapes Poster
- Evolution meeting, Norman, OK, June, 2011
Title: An Evaluation of Tree-to-Tree Distance Metrics used to Visualize Phylogenetic Tree Landscapes Poster
- Evolution meeting, Portland, OR, June, 2010
Title: The Evaluation of Dimensionality Reduction Methods to Characterize Phylogenetic Tree-Space Poster
- Computational Expo, Tallahassee, FL, April, 2010
Title: The Evaluation of Dimensionality Reduction Methods to Characterize Phylogenetic Tree-Space Poster