Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC
  via Variance Reduction   Replica exchange stochastic gradient Langevin dynamics (reSGLD) has shown
promise in accelerating the convergence in non-convex learning; however, an
excessively large correction for avoiding biases from noisy energy estimators
has limited the potential of the acceleration. To address this issue, we study
the variance reduction for noisy energy estimators, which promotes much more
effective swaps. Theoretically, we provide a non-asymptotic analysis on the
exponential acceleration for the underlying continuous-time Markov jump
process; moreover, we consider a generalized Girsanov theorem which includes
the change of Poisson measure to overcome the crude discretization based on the
Gr\"{o}wall's inequality and yields a much tighter error in the 2-Wasserstein
($\mathcal{W}_2$) distance. Numerically, we conduct extensive experiments and
obtain the state-of-the-art results in optimization and uncertainty estimates
for synthetic experiments and image data.

31
The categories of this paper are: ao-sci
5
The categories of this paper are: gr-qc
0
The categories of this paper are: hep-ph
10
The categories of this paper are: q-bio
3
The categories of this paper are: physics
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
14
The categories of this paper are: math-ph
19
The categories of this paper are: eess
8
The categories of this paper are: hep-ex
15
The categories of this paper are: nucl-ex
22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga
27
The categories of this paper are: comp-gas