Seminar: Deep Learning for Tabular Data

Tabular data has long been overlooked by deep learning research, despite being the most common data type in real-world machine learning applications. While deep learning methods excel on many ML applications, tabular data classification problems are still dominated by Gradient-Boosted Decision Trees. More recently, deep learning-based approaches have been proposed which showed remarkable efficiency and performance improvements. In this seminar, we will discuss this recent literature, exploring the most promising techniques and approaches for handling tabular data in deep learning.

Course type:Seminar
TimeEvery Tuesday from 14:15 - 16:00
Locationin-person; Room SR 00-006, Building 051
OrganizersHerilalaina Rakotoarison, Arbër Zela, Fabio Ferreira, Frank Hutter
RegistrationVia HISinOne
Web pageLink to the seminar webpage