Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Variance reduction for additive functional of Markov chains via
  martingale representations   In this paper we propose an efficient variance reduction approach for
additive functionals of Markov chains relying on a novel discrete time
martingale representation. Our approach is fully non-asymptotic and does not
require the knowledge of the stationary distribution (and even any type of
ergodicity) or specific structure of the underlying density. By rigorously
analyzing the convergence properties of the proposed algorithm, we show that
its cost-to-variance product is indeed smaller than one of the naive algorithm.
The numerical performance of the new method is illustrated for the
Langevin-type Markov Chain Monte Carlo (MCMC) methods.

22
The categories of this paper are: chao-dyn
5
The categories of this paper are: gr-qc
8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
21
The categories of this paper are: adap-org
1
The categories of this paper are: cs
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph
14
The categories of this paper are: math-ph
3
The categories of this paper are: physics
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg
10
The categories of this paper are: q-bio
2
The categories of this paper are: math
24
The categories of this paper are: dg-ga