Implementing Active Learning in Cybersecurity: Detecting Anomalies in Redacted Emails

no code implementations • 1 Mar 2023 • Mu-Huan Chung, Lu Wang, Sharon Li, Yuhong Yang, Calvin Giang, Khilan Jerath, Abhay Raman, David Lie, Mark Chignell

In this paper we present research results concerning the application of Active Learning to anomaly detection in redacted emails, comparing the utility of different methods for implementing active learning in this context.

Active Learning Anomaly Detection

MD-MTL: An Ensemble Med-Multi-Task Learning Package for DiseaseScores Prediction and Multi-Level Risk Factor Analysis

no code implementations • 5 Mar 2021 • Lu Wang, Haoyan Jiang, Mark Chignell

In this paper, we developed a new ensemble machine learning Python package based on multi-task learning (MTL), referred to as the Med-Multi-Task Learning (MD-MTL) package and applied it in predicting disease scores of patients, and in carrying out risk factor analysis on multiple subgroups of patients simultaneously.

BIG-bench Machine Learning Multi-Task Learning