A Method for Discovering Novel Classes in Tabular Data

Author:

Troisemaine Colin1,Flocon-Cholet Joachim1,Gosselin Stephane1,Vaton Sandrine2,Reiffers-Masson Alexandre2,Lemaire Vincent1

Affiliation:

1. Orange Labs,Lannion,France

2. IMT Atlantique,Department of Computer Science,Brest,France

Publisher

IEEE

Reference44 articles.

1. Vime: Extending the success of self- and semi-supervised learning to tabular domain;yoon;Advances in neural information processing systems,2020

2. Comparative accuracies of artificial neural networks and discriminant analysis in predicting forest cover types from cartographic variables

3. Evaluating the Impact of Categorical Data Encoding and Scaling on Neural Network Classification Performance: The Case of Repeat Consumption of Identical Cultural Goods

4. Optimization strategies in multi-task learning: Averaged or independent losses?;pascal;ArXiv,2021

5. A Survey on Transfer Learning

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A practical approach to novel class discovery in tabular data;Data Mining and Knowledge Discovery;2024-05-31

2. An Interactive Interface for Novel Class Discovery in Tabular Data;Lecture Notes in Computer Science;2023

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