A Riemannian BFGS Method for Nonconvex Optimization Problems. - Wen Huang 001; Pierre-Antoine Absil; Kyle A. Gallivan (ENUMATH, 2015)

Rank-constrained optimization: a Riemannian manifold approach. - Guifang Zhou; Wen Huang 001; Kyle A. Gallivan; Paul Van Dooren; Pierre-Antoine Absil (ESANN, 2015)

A Riemannian approach for computing geodesies in elastic shape analysis. - Yaqing You; Wen Huang 001; Kyle A. Gallivan; Pierre-Antoine Absil (GlobalSIP, 2015)

Weakly Correlated Sparse Components with Nearly Orthonormal Loadings. - Matthieu Genicot; Wen Huang 001; Nickolay T. Trendafilov (GSI, 2015)

A Riemannian symmetric rank-one trust-region method. - Wen Huang 001; Pierre-Antoine Absil; Kyle A. Gallivan (Math. Program., 2015)

A Broyden Class of Quasi-Newton Methods for Riemannian Optimization. - Wen Huang 001; Kyle A. Gallivan; Pierre-Antoine Absil (SIAM J. Optim., 2015)

Solving PhaseLift by Low-rank Riemannian Optimization Methods. - Wen Huang 001; Kyle A. Gallivan; Xiangxiong Zhang (ICCS, 2016)

A Riemannian Limited-memory BFGS Algorithm for Computing the Matrix Geometric Mean. - Xinru Yuan; Wen Huang 001; Pierre-Antoine Absil; Kyle A. Gallivan (ICCS, 2016)

A Riemannian rank-adaptive method for low-rank optimization. - Guifang Zhou; Wen Huang 001; Kyle A. Gallivan; Paul Van Dooren; Pierre-Antoine Absil (Neurocomputing, 2016)

Riemannian Optimization for Registration of Curves in Elastic Shape Analysis. - Wen Huang 001; Kyle A. Gallivan; Anuj Srivastava; Pierre-Antoine Absil (J. Math. Imaging Vis., 2016)

Visualizing phylogenetic tree landscapes. - James C. Wilgenbusch; Wen Huang 001; Kyle A. Gallivan (BMC Bioinform., 2017)

Intrinsic representation of tangent vectors and vector transports on matrix manifolds. - Wen Huang 001; Pierre-Antoine Absil; Kyle A. Gallivan (Numerische Mathematik, 2017)

Solving PhaseLift by Low-Rank Riemannian Optimization Methods for Complex Semidefinite Constraints. - Wen Huang 001; Kyle A. Gallivan; Xiangxiong Zhang (SIAM J. Sci. Comput., 2017)

A Riemannian BFGS Method Without Differentiated Retraction for Nonconvex Optimization Problems. - Wen Huang 001; Pierre-Antoine Absil; Kyle A. Gallivan (SIAM J. Optim., 2018)

ROPTLIB: An Object-Oriented C++ Library for Optimization on Riemannian Manifolds. - Wen Huang 001; Pierre-Antoine Absil; Kyle A. Gallivan; Paul Hand (ACM Trans. Math. Softw., 2018)

Community Detection by a Riemannian Projected Proximal Gradient Method. - Meng Wei; Wen Huang 001; Kyle A. Gallivan; Paul Van Dooren (CoRR, 2020)

Computing the matrix geometric mean: Riemannian versus Euclidean conditioning, implementation techniques, and a Riemannian BFGS method. - Xinru Yuan; Wen Huang 001; Pierre-Antoine Absil; Kyle A. Gallivan (Numer. Linear Algebra Appl., 2020)

Analysis of the Neighborhood Pattern Similarity Measure for the Role Extraction Problem. - Melissa Marchand; Kyle A. Gallivan; Wen Huang 001; Paul Van Dooren (SIAM J. Math. Data Sci., 2021)

Solving Stackelberg Prediction Game with Least Squares Loss via Spherically Constrained Least Squares Reformulation. - Jiali Wang; Wen Huang 001; Rujun Jiang; Xudong Li 004; Alex L. Wang (ICML, 2022)

On the analysis of optimization with fixed-rank matrices: a quotient geometric view. - Shuyu Dong; Bin Gao 007; Wen Huang 001; Kyle A. Gallivan (CoRR, 2022)

A Limited-Memory Riemannian Symmetric Rank-One Trust-Region Method with a Restart Strategy. - Wen Huang 001; Kyle A. Gallivan (J. Sci. Comput., 2022)

Riemannian proximal gradient methods. - Wen Huang 001; Ke Wei (Math. Program., 2022)

An extension of fast iterative shrinkage-thresholding algorithm to Riemannian optimization for sparse principal component analysis. - Wen Huang 001; Ke Wei (Numer. Linear Algebra Appl., 2022)

An inexact Riemannian proximal gradient method. - Wen Huang 001; Ke Wei (Comput. Optim. Appl., 2023)

Federated Learning on Riemannian Manifolds with Differential Privacy. - Zhenwei Huang; Wen Huang 001; Pratik Jawanpuria; Bamdev Mishra (CoRR, 2024)

Riemannian Federated Learning via Averaging Gradient Stream. - Zhenwei Huang; Wen Huang 001; Pratik Jawanpuria; Bamdev Mishra (CoRR, 2024)

Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-Order Convergence. - Yuetian Luo; Wen Huang 001; Xudong Li 004; Anru Zhang (Oper. Res., 2024)

An Operator-Splitting Optimization Approach for Phase-Field Simulation of Equilibrium Shapes of Crystals. - Zeyu Zhou; Wen Huang 001; Wei Jiang 008; Zhen Zhang 018 (SIAM J. Sci. Comput., 2024)

A Riemannian Proximal Newton Method. - Wutao Si; Pierre-Antoine Absil; Wen Huang 001; Rujun Jiang; Simon Vary (SIAM J. Optim., 2024)

An iterative algorithm for low-rank tensor completion problem with sparse noise and missing values. - Jianheng Chen; Wen Huang 001 (Numer. Linear Algebra Appl., 2024)

Rank-one approximation of a higher-order tensor by a Riemannian trust-region method. - Jianheng Chen; Wen Huang 001 (Comput. Optim. Appl., 2025)

A Riemannian Method on Quotient Manifolds for Solving Generalized Lyapunov Equations. - Zhenwei Huang; Wen Huang 001 (J. Sci. Comput., 2025)

A Riemannian Optimization Approach to Clustering Problems. - Wen Huang 001; Meng Wei; Kyle A. Gallivan; Paul Van Dooren (J. Sci. Comput., 2025)

The Exponential of Skew-Symmetric Matrices: A Nearby Inverse and Efficient Computation of Derivatives. - Zhifeng Deng; Pierre-Antoine Absil; Kyle A. Gallivan; Wen Huang 001 (CoRR, 2025)

SLRQA: A Sparse Low-Rank Quaternion Model for Color Image Processing with Convergence Analysis. - Zhanwang Deng; Yuqiu Su; Wen Huang 001 (J. Sci. Comput., 2025)