1. Jaroslav Kuchař and Vojtěch Svátek. Spotlighting Anomalies using Frequent Patterns
2. Bokai Cao, Mia Mao, Siim Viidu and Philip S. Yu. Collective Fraud Detection Capturing Inter-Transaction Dependency
3. Nalin Aggarwal, Alexander Statnikov and Chao Yuan. Automated System for Data Attribute Anomaly Detection
4. Michelle Miller and Robert Cezeaux. Sleuthing for adverse outcomes using anomaly detection
5. Parikshit Ram and Alexander Gray. Anomaly detection with density estimation trees
6. Matthew van Adelsberg and Christian Schwantes. Binned Kernels for Anomaly Detection in Multi-timescale Data using Gaussian Processes
7. Rasha Kashef. Ensemble-based Anomaly Detection Using Cooperative Agreement
8. Ira Cohen, Meir Toledano, Yonatan Ben Simhon and Inbal Tadeski. Real-time anomaly detection system for time series at scale
9. Youngjoon Ki and Ji Won Yoon. PD-FDS: Purchase Density based Online Credit Card Fraud Detection System
10. Daniel Lasaga and Prakash Santhana. Deep Learning to Detect Treatment Fraud amongst Healthcare Providers
11. Nian Yan, Xiaohang Zhang and Sriram Tirunellayi. Identity Fraud Detection with Distributed Graph Mining
12. Sen Tian and Panos Ipeirotis. Large-Scale Anomaly Detection
13. Jagan Kuntipuram, Vamsi Patil, Marco Jorge and Pedro Bizarro. Fraud-Trips: Detecting fraudsters that try to lay low

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