Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Sequential Learning of the Topological Ordering for the Linear
  Non-Gaussian Acyclic Model with Parametric Noise   Causal discovery, the learning of causality in a data mining scenario, has
been of strong scientific and theoretical interest as a starting point to
identify "what causes what?" Contingent on assumptions, it is sometimes
possible to identify an exact causal Directed Acyclic Graph (DAG), as opposed
to a Markov equivalence class of graphs that gives ambiguity of causal
directions. The focus of this paper is on one such case: a linear structural
equation model with non-Gaussian noise, a model known as the Linear
Non-Gaussian Acyclic Model (LiNGAM). Given a specified parametric noise model,
we develop a novel sequential approach to estimate the causal ordering of a
DAG. At each step of the procedure, only simple likelihood ratio scores are
calculated on regression residuals to decide the next node to append to the
current partial ordering. Under mild assumptions, the population version of our
procedure provably identifies a true ordering of the underlying causal DAG. We
provide extensive numerical evidence to demonstrate that our sequential
procedure is scalable to cases with possibly thousands of nodes and works well
for high-dimensional data. We also conduct an application to a single-cell gene
expression dataset to demonstrate our estimation procedure.

15
The categories of this paper are: nucl-ex
37
The categories of this paper are: supr-con
30
The categories of this paper are: q-alg
17
The categories of this paper are: q-fin
34
The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
18
The categories of this paper are: econ
3
The categories of this paper are: physics
19
The categories of this paper are: eess
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
21
The categories of this paper are: adap-org
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th