1. Accelerated gradient methods for geodesically convex optimization: Tractable algorithms and convergence analysis (with Insoon Yang). [Paper]
   Note: Errors in Eq. 6 and Thm. 5.6 have been corrected (thanks to the suggestion by Prof. Ken’ichiro Tanaka.
2. Unifying Nesterov’s accelerated gradient methods for convex and strongly convex objective functions (with Insoon Yang). [Paper] [Notes and Errata]
   Note: If you cite “Unified AGM ODE” or “Unified Bregman Lagrangian flow” in this paper, please consider also citing “NAG flow” in [Luo & Chen, 2021, Section 3] (see Notes and Errata).
3. Convergence analysis of ODE models for accelerated first-order methods via positive semidefinite kernels (with Insoon Yang). [Paper] [Notes]
4. A proof of the exact convergence rate of gradient descent. [Paper] [Notes and Errata]
5. Horospherically Convex Optimization on Hadamard Manifolds Part I: Analysis and Algorithms (with Christopher Criscitiello). [Paper]