Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Accelerating Primal-dual Methods for Regularized Markov Decision
  Processes   Entropy regularized Markov decision processes have been widely used in
reinforcement learning. This paper is concerned with the primal-dual
formulation of the entropy regularized problems. Standard first-order methods
suffer from slow convergence due to the lack of strict convexity and concavity.
To address this issue, we first introduce a new quadratically convexified
primal-dual formulation. The natural gradient ascent descent of the new
formulation enjoys global convergence guarantee and exponential convergence
rate. We also propose a new interpolating metric that further accelerates the
convergence significantly. Numerical results are provided to demonstrate the
performance of the proposed methods under multiple settings.

22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
23
The categories of this paper are: solv-int
5
The categories of this paper are: gr-qc
34
The categories of this paper are: chem-ph
9
The categories of this paper are: nlin
24
The categories of this paper are: dg-ga
12
The categories of this paper are: nucl-th
30
The categories of this paper are: q-alg
29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
28
The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph