Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: CPM-sensitive AUC for CTR prediction   The prediction of click-through rate (CTR) is crucial for industrial
applications, such as online advertising. AUC is a commonly used evaluation
indicator for CTR models. For advertising platforms, online performance is
generally evaluated by CPM. However, in practice, AUC often improves in offline
evaluation, but online CPM does not. As a result, a huge waste of precious
online traffic and human costs has been caused. This is because there is a gap
between offline AUC and online CPM. AUC can only reflect the order on CTR, but
it does not reflect the order of CTR*Bid. Moreover, the bids of different
advertisements are different, so the loss of income caused by different
reverse-order pair is also different. For this reason, we propose the
CPM-sensitive AUC (csAUC) to solve all these problems. We also give the csAUC
calculation method based on dynamic programming. It can fully support the
calculation of csAUC on large-scale data in real-world applications.

26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
2
The categories of this paper are: math
25
The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
17
The categories of this paper are: q-fin
22
The categories of this paper are: chao-dyn
28
The categories of this paper are: alg-geom
14
The categories of this paper are: math-ph
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
37
The categories of this paper are: supr-con
15
The categories of this paper are: nucl-ex