Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multitask Learning using Task Clustering with Applications to Predictive
  Modeling and GWAS of Plant Varieties   Inferring predictive maps between multiple input and multiple output
variables or tasks has innumerable applications in data science. Multi-task
learning attempts to learn the maps to several output tasks simultaneously with
information sharing between them. We propose a novel multi-task learning
framework for sparse linear regression, where a full task hierarchy is
automatically inferred from the data, with the assumption that the task
parameters follow a hierarchical tree structure. The leaves of the tree are the
parameters for individual tasks, and the root is the global model that
approximates all the tasks. We apply the proposed approach to develop and
evaluate: (a) predictive models of plant traits using large-scale and automated
remote sensing data, and (b) GWAS methodologies mapping such derived phenotypes
in lieu of hand-measured traits. We demonstrate the superior performance of our
approach compared to other methods, as well as the usefulness of discovering
hierarchical groupings between tasks. Our results suggest that richer genetic
mapping can indeed be obtained from the remote sensing data. In addition, our
discovered groupings reveal interesting insights from a plant science
perspective.

2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
21
The categories of this paper are: adap-org
25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
24
The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
18
The categories of this paper are: econ
15
The categories of this paper are: nucl-ex
3
The categories of this paper are: physics
29
The categories of this paper are: funct-an
37
The categories of this paper are: supr-con
20
The categories of this paper are: acc-phys
11
The categories of this paper are: hep-lat