Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Context-dependent Ranking and Selection under a Bayesian Framework   We consider a context-dependent ranking and selection problem. The best
design is not universal but depends on the contexts. Under a Bayesian
framework, we develop a dynamic sampling scheme for context-dependent
optimization (DSCO) to efficiently learn and select the best designs in all
contexts. The proposed sampling scheme is proved to be consistent. Numerical
experiments show that the proposed sampling scheme significantly improves the
efficiency in context-dependent ranking and selection.

1
The categories of this paper are: cs
18
The categories of this paper are: econ
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio
19
The categories of this paper are: eess
5
The categories of this paper are: gr-qc
32
The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
9
The categories of this paper are: nlin
28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
22
The categories of this paper are: chao-dyn
2
The categories of this paper are: math