50 citations · 128 across the 32 of their papers we have counts for
8 papers · 1 filter
Uncertainty-aware Human Mobility Modeling and Anomaly Detection
Haomin Wen, Shurui Cao, Zeeshan Rasheed +2
Given the temporal GPS coordinates from a large set of human agents, how can we model their mobility behavior toward effective anomaly (e.g. bad-actor or malicious behavior) detect…
FoMo-0D: A Foundation Model for Zero-shot Tabular Outlier Detection
Yuchen Shen, Haomin Wen, Leman Akoglu
Outlier detection (OD) has a vast literature as it finds numerous real-world applications. Being an unsupervised task, model selection is a key bottleneck for OD without label supe…
Outlier Detection Bias Busted: Understanding Sources of Algorithmic Bias through Data-centric Factors
Xueying Ding, Rui Xi, Leman Akoglu
The astonishing successes of ML have raised growing concern for the fairness of modern methods when deployed in real world settings. However, studies on fairness have mostly focuse…
End-To-End Self-Tuning Self-Supervised Time Series Anomaly Detection
Boje Deforce, Meng-Chieh Lee, Bart Baesens +3
Time series anomaly detection (TSAD) finds many applications such as monitoring environmental sensors, industry KPIs, patient biomarkers, etc. A two-fold challenge for TSAD is a ve…
On the Detection of Reviewer-Author Collusion Rings From Paper Bidding
Steven Jecmen, Nihar B. Shah, Fei Fang +1
A major threat to the peer-review systems of computer science conferences is the existence of "collusion rings" between reviewers. In such collusion rings, reviewers who have also…
Descriptive Kernel Convolution Network with Improved Random Walk Kernel
Meng-Chieh Lee, Lingxiao Zhao, Leman Akoglu
Graph kernels used to be the dominant approach to feature engineering for structured data, which are superseded by modern GNNs as the former lacks learnability. Recently, a suite o…