Solving graph equipartition SDPs on an algebraic variety T Tang, KC Toh Mathematical Programming 204 (1), 299-347, 2024 | 13 | 2024 |
Self-adaptive ADMM for semi-strongly convex problems T Tang, KC Toh Mathematical Programming Computation 16 (1), 113-150, 2024 | 10 | 2024 |
A feasible method for general convex low-rank SDP problems T Tang, KC Toh SIAM Journal on Optimization 34 (3), 2169-2200, 2024 | 9 | 2024 |
Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition C Lee, L Liang, T Tang, KC Toh Journal of Machine Learning Research 25 (379), 1-52, 2024 | 8 | 2024 |
A feasible method for solving an SDP relaxation of the quadratic knapsack problem T Tang, KC Toh Mathematics of Operations Research 49 (1), 19-39, 2024 | 6 | 2024 |
A Riemannian Dimension-Reduced Second-Order Method with Application in Sensor Network Localization T Tang, KC Toh, N Xiao, Y Ye SIAM Journal on Scientific Computing 46 (3), A2025-A2046, 2024 | 4 | 2024 |
Minimizing cycles in tournaments and normalized -norms J Ma, T Tang arXiv preprint arXiv:2011.14142, 2020 | 2 | 2020 |
Escaping spurious local minima of low-rank matrix factorization through convex lifting C Lee, L Liang, T Tang, KC Toh arXiv preprint arXiv:2204.14067, 2022 | 1 | 2022 |
A low-rank augmented Lagrangian method for doubly nonnegative relaxations of mixed-binary quadratic programs D Hou, T Tang, KC Toh arXiv preprint arXiv:2502.13849, 2025 | | 2025 |
A Bregman ADMM for Bethe variational problem Y Khoo, T Tang, KC Toh arXiv preprint arXiv:2502.04613, 2025 | | 2025 |
Optimization over convex polyhedra via Hadamard parametrizations T Tang, KC Toh Mathematical Programming, 1-41, 2024 | | 2024 |
Exploring chordal sparsity in semidefinite programming with sparse plus low-rank data matrices T Tang, KC Toh arXiv preprint arXiv:2410.23849, 2024 | | 2024 |
Monochromatic subgraphs in iterated triangulations J Ma, T Tang, X Yu arXiv preprint arXiv:1912.00123, 2019 | | 2019 |