Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Functional mixture-of-experts for classification   We develop a mixtures-of-experts (ME) approach to the multiclass
classification where the predictors are univariate functions. It consists of a
ME model in which both the gating network and the experts network are
constructed upon multinomial logistic activation functions with functional
inputs. We perform a regularized maximum likelihood estimation in which the
coefficient functions enjoy interpretable sparsity constraints on targeted
derivatives. We develop an EM-Lasso like algorithm to compute the regularized
MLE and evaluate the proposed approach on simulated and real data.

12
The categories of this paper are: nucl-th
20
The categories of this paper are: acc-phys
34
The categories of this paper are: chem-ph
0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
26
The categories of this paper are: bayes-an
11
The categories of this paper are: hep-lat
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
6
The categories of this paper are: astro-ph
24
The categories of this paper are: dg-ga
3
The categories of this paper are: physics
18
The categories of this paper are: econ
14
The categories of this paper are: math-ph
37
The categories of this paper are: supr-con