Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Scalable Nonlinear Learning with Adaptive Polynomial Expansions   Can we effectively learn a nonlinear representation in time comparable to
linear learning? We describe a new algorithm that explicitly and adaptively
expands higher-order interaction features over base linear representations. The
algorithm is designed for extreme computational efficiency, and an extensive
experimental study shows that its computation/prediction tradeoff ability
compares very favorably against strong baselines.

10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
2
The categories of this paper are: math
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an
19
The categories of this paper are: eess
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics
13
The categories of this paper are: quant-ph
29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom