Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Nonparametric Link Prediction in Dynamic Networks   We propose a non-parametric link prediction algorithm for a sequence of graph
snapshots over time. The model predicts links based on the features of its
endpoints, as well as those of the local neighborhood around the endpoints.
This allows for different types of neighborhoods in a graph, each with its own
dynamics (e.g, growing or shrinking communities). We prove the consistency of
our estimator, and give a fast implementation based on locality-sensitive
hashing. Experiments with simulated as well as five real-world dynamic graphs
show that we outperform the state of the art, especially when sharp
fluctuations or non-linearities are present.

2
The categories of this paper are: math
9
The categories of this paper are: nlin
30
The categories of this paper are: q-alg
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th
29
The categories of this paper are: funct-an
27
The categories of this paper are: comp-gas
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
7
The categories of this paper are: hep-th
33
The categories of this paper are: plasm-ph
4
The categories of this paper are: cond-mat