Na Zou

PyODDS: An End-to-end Outlier Detection System with Automated Machine Learning

2020 · Companion Proceedings of the Web Conference 2020

Outlier detection is an important task for various data mining applications. Current outlier detection techniques are often manually designed for specific domains, requiring large human efforts of database setup, algorithm selection, and hyper-parameter tuning. To …

CODA: Temporal Domain Generalization via Concept Drift Simulator

2023 · arXiv (Cornell University)

In real-world applications, machine learning models often become obsolete due to shifts in the joint distribution arising from underlying temporal trends, a phenomenon known as the "concept drift". Existing works propose model-specific strategies to achieve …