Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The Wang-Landau Algorithm as Stochastic Optimization and Its
  Acceleration   We show that the Wang-Landau algorithm can be formulated as a stochastic
gradient descent algorithm minimizing a smooth and convex objective function,
of which the gradient is estimated using Markov chain Monte Carlo iterations.
The optimization formulation provides us a new way to establish the convergence
rate of the Wang-Landau algorithm, by exploiting the fact that almost surely,
the density estimates (on the logarithmic scale) remain in a compact set, upon
which the objective function is strongly convex. The optimization viewpoint
motivates us to improve the efficiency of the Wang-Landau algorithm using
popular tools including the momentum method and the adaptive learning rate
method. We demonstrate the accelerated Wang-Landau algorithm on a
two-dimensional Ising model and a two-dimensional ten-state Potts model.

19
The categories of this paper are: eess
6
The categories of this paper are: astro-ph
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg
12
The categories of this paper are: nucl-th
35
The categories of this paper are: mtrl-th
29
The categories of this paper are: funct-an
24
The categories of this paper are: dg-ga
20
The categories of this paper are: acc-phys
5
The categories of this paper are: gr-qc
8
The categories of this paper are: hep-ex
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics
17
The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat