Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Soft-Sensing ConFormer: A Curriculum Learning-based Convolutional
  Transformer   Over the last few decades, modern industrial processes have investigated
several cost-effective methodologies to improve the productivity and yield of
semiconductor manufacturing. While playing an essential role in facilitating
real-time monitoring and control, the data-driven soft-sensors in industries
have provided a competitive edge when augmented with deep learning approaches
for wafer fault-diagnostics. Despite the success of deep learning methods
across various domains, they tend to suffer from bad performance on
multi-variate soft-sensing data domains. To mitigate this, we propose a
soft-sensing ConFormer (CONvolutional transFORMER) for wafer fault-diagnostic
classification task which primarily consists of multi-head convolution modules
that reap the benefits of fast and light-weight operations of convolutions, and
also the ability to learn the robust representations through multi-head design
alike transformers. Another key issue is that traditional learning paradigms
tend to suffer from low performance on noisy and highly-imbalanced soft-sensing
data. To address this, we augment our soft-sensing ConFormer model with a
curriculum learning-based loss function, which effectively learns easy samples
in the early phase of training and difficult ones later. To further demonstrate
the utility of our proposed architecture, we performed extensive experiments on
various toolsets of Seagate Technology's wafer manufacturing process which are
shared openly along with this work. To the best of our knowledge, this is the
first time that curriculum learning-based soft-sensing ConFormer architecture
has been proposed for soft-sensing data and our results show strong promise for
future use in soft-sensing research domain.

17
The categories of this paper are: q-fin
15
The categories of this paper are: nucl-ex
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th
26
The categories of this paper are: bayes-an
21
The categories of this paper are: adap-org
9
The categories of this paper are: nlin
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
18
The categories of this paper are: econ
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
25
The categories of this paper are: patt-sol