For modern gradient-based optimization, a developmental landmark is
Nest...
Since optimization on Riemannian manifolds relies on the chosen metric, ...
The high-resolution differential equation framework has been proven to b...
We propose Riemannian preconditioned algorithms for the tensor completio...
In this paper, we revisit the class of iterative shrinkage-thresholding
...
Nesterov's accelerated gradient descent (NAG) is one of the milestones i...
For first-order smooth optimization, the research on the acceleration
ph...
We study in this paper the function approximation error of linear
interp...
In the history of first-order algorithms, Nesterov's accelerated gradien...
This paper studies generalized truncated moment problems with unbounded ...