Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Convergence of iterates for first-order optimization algorithms with
  inertia and Hessian driven damping   In a Hilbert space setting, for convex optimization, we show the convergence
of the iterates to optimal solutions for a class of accelerated first-order
algorithms. They can be interpreted as discrete temporal versions of an
inertial dynamic involving both viscous damping and Hessian-driven damping. The
asymptotically vanishing viscous damping is linked to the accelerated gradient
method of Nesterov while the Hessian driven damping makes it possible to
significantly attenuate the oscillations. By treating the Hessian-driven
damping as the time derivative of the gradient term, this gives, in discretized
form, first-order algorithms. These results complement the previous work of the
authors where it was shown the fast convergence of the values, and the fast
convergence towards zero of the gradients.

31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
15
The categories of this paper are: nucl-ex
26
The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
6
The categories of this paper are: astro-ph
22
The categories of this paper are: chao-dyn
20
The categories of this paper are: acc-phys
3
The categories of this paper are: physics
1
The categories of this paper are: cs
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
28
The categories of this paper are: alg-geom