Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Identifying Best Interventions through Online Importance Sampling   Motivated by applications in computational advertising and systems biology,
we consider the problem of identifying the best out of several possible soft
interventions at a source node $V$ in an acyclic causal directed graph, to
maximize the expected value of a target node $Y$ (located downstream of $V$).
Our setting imposes a fixed total budget for sampling under various
interventions, along with cost constraints on different types of interventions.
We pose this as a best arm identification bandit problem with $K$ arms where
each arm is a soft intervention at $V,$ and leverage the information leakage
among the arms to provide the first gap dependent error and simple regret
bounds for this problem. Our results are a significant improvement over the
traditional best arm identification results. We empirically show that our
algorithms outperform the state of the art in the Flow Cytometry data-set, and
also apply our algorithm for model interpretation of the Inception-v3 deep net
that classifies images.

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The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
11
The categories of this paper are: hep-lat
30
The categories of this paper are: q-alg
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
5
The categories of this paper are: gr-qc
25
The categories of this paper are: patt-sol
19
The categories of this paper are: eess
3
The categories of this paper are: physics
6
The categories of this paper are: astro-ph
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org