LF-Transformer: Latent Factorizer Transformer for Tabular Learning

LF-Transformer: Latent Factorizer Transformer for Tabular Learning

The field of deep learning for tabular datasets has made significant strides in recent times. Previously, gradient boosting and decision tree algorithms had been the go-to options for processing such datasets due to their superior performance. However, deep learning has now reached a level of develo...

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Bibliographic Details
Main Authors: Kwangtek Na, Ju-Hong Lee, Eunchan Kim
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Tabular dataset
tabular learning
self-attention
row-wise attention
column-wise attention
matrix factorization
Online Access:https://ieeexplore.ieee.org/document/10401112/

Internet

https://ieeexplore.ieee.org/document/10401112/

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