Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Framework for Adaptive MCMC Targeting Multimodal Distributions   We propose a new Monte Carlo method for sampling from multimodal
distributions. The idea of this technique is based on splitting the task into
two: finding the modes of a target distribution $\pi$ and sampling, given the
knowledge of the locations of the modes. The sampling algorithm relies on steps
of two types: local ones, preserving the mode; and jumps to regions associated
with different modes. Besides, the method learns the optimal parameters of the
algorithm while it runs, without requiring user intervention. Our technique
should be considered as a flexible framework, in which the design of moves can
follow various strategies known from the broad MCMC literature.
  In order to design an adaptive scheme that facilitates both local and jump
moves, we introduce an auxiliary variable representing each mode and we define
a new target distribution $\tilde{\pi}$ on an augmented state space
$\mathcal{X}~\times~\mathcal{I}$, where $\mathcal{X}$ is the original state
space of $\pi$ and $\mathcal{I}$ is the set of the modes. As the algorithm runs
and updates its parameters, the target distribution $\tilde{\pi}$ also keeps
being modified. This motivates a new class of algorithms, Auxiliary Variable
Adaptive MCMC. We prove general ergodic results for the whole class before
specialising to the case of our algorithm.

15
The categories of this paper are: nucl-ex
4
The categories of this paper are: cond-mat
5
The categories of this paper are: gr-qc
27
The categories of this paper are: comp-gas
21
The categories of this paper are: adap-org
3
The categories of this paper are: physics
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
14
The categories of this paper are: math-ph
6
The categories of this paper are: astro-ph
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an
9
The categories of this paper are: nlin
35
The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int