@inproceedings{wang2022automated,
author = {Wang, Chi and Wu, Qingyun and Liu, Xueqing and Quintanilla, Luis},
title = {Automated Machine Learning & Tuning with FLAML},
booktitle = {ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022)},
year = {2022},
month = {August},
abstract = {In this tutorial, we will provide an in-depth and hands-on tutorial on Automated Machine Learning & Tuning with a fast python library FLAML. We will start with an overview of the AutoML problem and the FLAML library. In the first half of the tutorial, we will then give a hands-on tutorial on how to use FLAML to automate typical machine learning tasks in an end-to-end manner with different customization options and how to perform general tuning tasks on user-defined functions. In the second half of the tutorial, we will introduce several advanced functionalities of the library. For example, zero-shot AutoML, fair AutoML, and online AutoML. We will close the tutorial with several open problems, and challenges learned from AutoML practice.},
url = {http://approjects.co.za/?big=en-us/research/publication/automated-machine-learning-tuning-with-flaml/},
}