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20182021
most citedA Human-Grounded Evaluation of SHAP for Alert Processing

20 citations · 39 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SI2021

The Banking Transactions Dataset and its Comparative Analysis with Scale-free Networks

Akrati Saxena, Yulong Pei, Jan Veldsink +3

We construct a network of 1.6 million nodes from banking transactions of users of Rabobank. We assign two weights on each edge, which are the aggregate transferred amount and the t…

cs.LG2020★ 7 cited

ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks

Yulong Pei, Tianjin Huang, Werner van Ipenburg +1

Effectively detecting anomalous nodes in attributed networks is crucial for the success of many real-world applications such as fraud and intrusion detection. Existing approaches h…

cs.LG2019★ 5 cited

Case-Based Reasoning for Assisting Domain Experts in Processing Fraud Alerts of Black-Box Machine Learning Models

Hilde J. P. Weerts, Werner van Ipenburg, Mykola Pechenizkiy

In many contexts, it can be useful for domain experts to understand to what extent predictions made by a machine learning model can be trusted. In particular, estimates of trustwor…

cs.LG2019★ 20 cited

A Human-Grounded Evaluation of SHAP for Alert Processing

Hilde J. P. Weerts, Werner van Ipenburg, Mykola Pechenizkiy

In the past years, many new explanation methods have been proposed to achieve interpretability of machine learning predictions. However, the utility of these methods in practical a…

cs.IR2018★ 7 cited

Looking Deeper into Deep Learning Model: Attribution-based Explanations of TextCNN

Wenting Xiong, Iftitahu Ni'mah, Juan M. G. Huesca +3

Layer-wise Relevance Propagation (LRP) and saliency maps have been recently used to explain the predictions of Deep Learning models, specifically in the domain of text classificati…