Challenges in deploying machine learning: a survey of case studies

A Paleyes, RG Urma, ND Lawrence - ACM computing surveys, 2022 - dl.acm.org
In recent years, machine learning has transitioned from a field of academic research interest
to a field capable of solving real-world business problems. However, the deployment of …

Urban anomaly analytics: Description, detection, and prediction

M Zhang, T Li, Y Yu, Y Li, P Hui… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Urban anomalies may result in loss of life or property if not handled properly. Automatically
alerting anomalies in their early stage or even predicting anomalies before happening is of …

Gamut: A design probe to understand how data scientists understand machine learning models

F Hohman, A Head, R Caruana, R DeLine… - Proceedings of the …, 2019 - dl.acm.org
Without good models and the right tools to interpret them, data scientists risk making
decisions based on hidden biases, spurious correlations, and false generalizations. This …

Heat map visualisation of fire incidents based on transformed sigmoid risk model

D Liu, Z Xu, Y Zhou, C Fan - Fire Safety Journal, 2019 - Elsevier
Fire is one of the most frequent disasters that threaten public safety and ecological balance.
Heat maps have been used as a common visualisation method in many scientific fields but …

From symbols to embeddings: A tale of two representations in computational social science

H Chen, C Yang, X Zhang, Z Liu… - Journal of Social …, 2021 - ieeexplore.ieee.org
Computational Social Science (CSS), aiming at utilizing computational methods to address
social science problems, is a recent emerging and fast-develo** field. The study of CSS is …