Publications

Quotient geometry of tensor ring decomposition. arXiv:2601.21874, (2026).

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A space-decoupling framework for optimization on bounded-rank matrices with orthogonally invariant constraints. Mathematical Programming, (2026), accepted.

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Variational analysis of determinantal varieties. arXiv:2511.22613, (2025).

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Normalized tensor train decomposition. arXiv:2511.04369, (2025).

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Distributed retraction-free and communication-efficient optimization on the Stiefel manifold. Proceedings of the 42st International Conference on Machine Learning (ICML 2025), PMLR 267 (2025), 56281–56318.

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Optimization on product manifolds under a preconditioned metric. SIAM Journal on Matrix Analysis and Applications, 46-3 (2025), 1816–1845.

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Riemannian optimization for Holevo capacity. 2025 IEEE International Symposium on Information Theory (ISIT), (2025), 1–6.

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First-order methods on bounded-rank tensors converging to stationary points. arXiv:2503.04523, (2025).

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Low-rank optimization on Tucker tensor varieties. Mathematical Programming, 214 (2025), 357–407.

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LancBiO: dynamic Lanczos-aided bilevel optimization via Krylov subspace. The 13th International Conference on Learning Representations (ICLR 2025), (2025).

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Bilevel reinforcement learning via the development of hyper-gradient without lower-level convexity. Proceedings of The 28th International Conference on Artificial Intelligence and Statistics (AISTATS 2025), PMLR 258 (2025), 4780–4788.

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Infeasible deterministic, stochastic, and variance-reduction algorithms for optimization under orthogonality constraints. Journal of Machine Learning Research, 25(389) (2024), 1–38.

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Desingularization of bounded-rank tensor sets. arXiv:2411.14093, (2024).

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Symplectic Stiefel manifold: tractable metrics, second-order geometry and Newton's methods. arXiv:2406.14299, (2024).

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Optimization without retraction on the random generalized Stiefel manifold. Proceedings of the 41st International Conference on Machine Learning (ICML 2024), PMLR 235 (2024), 49226–49248.

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Riemannian preconditioned algorithms for tensor completion via tensor ring decomposition. Computational Optimization and Applications, 88 (2024), 443–468.

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Optimization on the symplectic Stiefel manifold: SR decomposition-based retraction and applications. Linear Algebra and Its Applications, 682 (2024), 50–85.

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Alternating minimization algorithms for graph regularized tensor completion. arXiv:2008.12876, (2023).

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Optimization flows landing on the Stiefel manifold. 25th IFAC Symposium on Mathematical Theory of Networks and Systems (MTNS 2022), IFAC-PapersOnLine, 55-30 (2022), 25–30.

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On the analysis of optimization with fixed-rank matrices: a quotient geometric view. arXiv:2203.06765, (2022).

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An orthogonalization-free parallelizable framework for all-electron calculations in density functional theory. SIAM Journal on Scientific Computing, 44-3 (2022), B723–B745.

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New Riemannian preconditioned algorithms for tensor completion via polyadic decomposition. SIAM Journal on Matrix Analysis and Applications, 43-2 (2022), 840–866.

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A Riemannian rank-adaptive method for low-rank matrix completion. Computational Optimization and Applications, 81 (2022), 67–90.

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Computing symplectic eigenpairs of symmetric positive-definite matrices via trace minimization and Riemannian optimization. SIAM Journal on Matrix Analysis and Applications, 42-4 (2021), 1732–1757.

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Geometry of the symplectic Stiefel manifold endowed with the Euclidean metric. Geometric Science of Information: 5th International Conference (GSI 2021), Lecture Notes in Computer Science, 12829 (2021), 789–796.

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Riemannian optimization on the symplectic Stiefel manifold. SIAM Journal on Optimization, 31-2 (2021), 1546–1575.

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Multipliers correction methods for optimization problems over the Stiefel manifold. CSIAM Transactions on Applied Mathematics, 2-3 (2021), 508–531.

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Parallelizable algorithms for optimization problems with orthogonality constraints. SIAM Journal on Scientific Computing, 41-3 (2019), A1949–A1983.

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A new first-order algorithmic framework for optimization problems with orthogonality constraints. SIAM Journal on Optimization, 28-1 (2018), 302–332.

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First-order algorithms for optimization problems with orthogonality constraints. OR Transactions (in Chinese), 21-4 (2017), 57–68.

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On the Łojasiewicz exponent of the quadratic sphere constrained optimization problem. arXiv:1611.08781, (2016).

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