228 citations · 813 across the 67 of their papers we have counts for
7 papers · 2 filters
Toward Unsupervised Outlier Model Selection
Yue Zhao, Sean Zhang, Leman Akoglu
Today there exists no shortage of outlier detection algorithms in the literature, yet the complementary and critical problem of unsupervised outlier model selection (UOMS) is vastl…
A Practical, Progressively-Expressive GNN
Lingxiao Zhao, Louis Härtel, Neil Shah +1
Message passing neural networks (MPNNs) have become a dominant flavor of graph neural networks (GNNs) in recent years. Yet, MPNNs come with notable limitations; namely, they are at…
Graph Anomaly Detection with Unsupervised GNNs
Lingxiao Zhao, Saurabh Sawlani, Arvind Srinivasan +1
Graph-based anomaly detection finds numerous applications in the real-world. Thus, there exists extensive literature on the topic that has recently shifted toward deep detection mo…
D.MCA: Outlier Detection with Explicit Micro-Cluster Assignments
Shuli Jiang, Robson Leonardo Ferreira Cordeiro, Leman Akoglu
How can we detect outliers, both scattered and clustered, and also explicitly assign them to respective micro-clusters, without knowing apriori how many micro-clusters exist? How c…
Hyperparameter Optimization for Unsupervised Outlier Detection
Yue Zhao, Leman Akoglu
Given an unsupervised outlier detection (OD) algorithm, how can we optimize its hyperparameter(s) (HP) on a new dataset, without any labels? In this work, we address this challengi…
Data Augmentation is a Hyperparameter: Cherry-picked Self-Supervision for Unsupervised Anomaly Detection is Creating the Illusion of Success
Jaemin Yoo, Tiancheng Zhao, Leman Akoglu
Self-supervised learning (SSL) has emerged as a promising alternative to create supervisory signals to real-world problems, avoiding the extensive cost of manual labeling. SSL is p…
Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution
Xueying Ding, Lingxiao Zhao, Leman Akoglu
Outlier detection (OD) literature exhibits numerous algorithms as it applies to diverse domains. However, given a new detection task, it is unclear how to choose an algorithm to us…