Online Probabilistic Label Trees

January 22, 2021

Abstract

We introduce online probabilistic label trees (OPLTs), an algorithm that trains a label tree classifier in a fully online manner, without any prior knowledge about the number of training instances, their features and labels. OPLTs are characterized by low time and space complexity as well as strong theoretical guarantees. They can be used for online multi-label and multi-class classification, including the very challenging scenarios of one- or few-shot learning. We demonstrate the attractiveness of OPLTs in a wide empirical study on several instances of the tasks mentioned above.

Download

Publication Type

Paper

Conference / Journal Name

AISTATS 2021

Authors

Kalina Jasinska-Kobus

Marek Wydmuch

Devanathan Thiruvenkatachari

Krzysztof Dembczynski

BibTeX


@inproceedings{
    author = {},
    title = {‌Online Probabilistic Label Trees‌},
    booktitle = {Proceedings of AISTATS 2021‌},
    year = {‌2021‌}
}