Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Robust LogitBoost and Adaptive Base Class (ABC) LogitBoost   Logitboost is an influential boosting algorithm for classification. In this
paper, we develop robust logitboost to provide an explicit formulation of
tree-split criterion for building weak learners (regression trees) for
logitboost. This formulation leads to a numerically stable implementation of
logitboost. We then propose abc-logitboost for multi-class classification, by
combining robust logitboost with the prior work of abc-boost. Previously,
abc-boost was implemented as abc-mart using the mart algorithm. Our extensive
experiments on multi-class classification compare four algorithms: mart,
abcmart, (robust) logitboost, and abc-logitboost, and demonstrate the
superiority of abc-logitboost. Comparisons with other learning methods
including SVM and deep learning are also available through prior publications.

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The categories of this paper are: funct-an
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The categories of this paper are: dg-ga
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
9
The categories of this paper are: nlin
25
The categories of this paper are: patt-sol
8
The categories of this paper are: hep-ex
7
The categories of this paper are: hep-th
15
The categories of this paper are: nucl-ex
13
The categories of this paper are: quant-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: atom-ph
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The categories of this paper are: mtrl-th
3
The categories of this paper are: physics
10
The categories of this paper are: q-bio
21
The categories of this paper are: adap-org