research
∙
08/19/2023
Robust Fraud Detection via Supervised Contrastive Learning
Deep learning models have recently become popular for detecting maliciou...
share
research
∙
03/04/2023
Achieving Counterfactual Fairness for Anomaly Detection
Ensuring fairness in anomaly detection models has received much attentio...
research
∙
12/08/2022
On Interpretable Anomaly Detection Using Causal Algorithmic Recourse
As many deep anomaly detection models have been deployed in the real-wor...
research
∙
11/12/2022
Generating Textual Adversaries with Minimal Perturbation
Many word-level adversarial attack approaches for textual data have been...
research
∙
11/08/2022
Robust Unstructured Knowledge Access in Conversational Dialogue with ASR Errors
Performance of spoken language understanding (SLU) can be degraded with ...
research
∙
10/09/2022
Fine-grained Anomaly Detection in Sequential Data via Counterfactual Explanations
Anomaly detection in sequential data has been studied for a long time be...
research
∙
02/15/2022
Trustworthy Anomaly Detection: A Survey
Anomaly detection has a wide range of real-world applications, such as b...
research
∙
03/07/2021
LogBERT: Log Anomaly Detection via BERT
Detecting anomalous events in online computer systems is crucial to prot...
research
∙
05/25/2020
Deep Learning for Insider Threat Detection: Review, Challenges and Opportunities
Insider threats, as one type of the most challenging threats in cyberspa...
research
∙
11/12/2019
Identifying Hidden Buyers in Darknet Markets via Dirichlet Hawkes Process
The darknet markets are notorious black markets in cyberspace, which inv...
research
∙
11/11/2019
Achieving Differential Privacy in Vertically Partitioned Multiparty Learning
Preserving differential privacy has been well studied under centralized ...
research
∙
10/08/2019
Insider Threat Detection via Hierarchical Neural Temporal Point Processes
Insiders usually cause significant losses to organizations and are hard ...
research
∙
09/12/2018
SAFE: A Neural Survival Analysis Model for Fraud Early Detection
Many online platforms have deployed anti-fraud systems to detect and pre...
research
∙
05/28/2018
FairGAN: Fairness-aware Generative Adversarial Networks
Fairness-aware learning is increasingly important in data mining. Discri...
research
∙
03/05/2018
One-Class Adversarial Nets for Fraud Detection
Many online applications, such as online social networks or knowledge ba...
research
∙
06/03/2017
Wikipedia Vandal Early Detection: from User Behavior to User Embedding
Wikipedia is the largest online encyclopedia that allows anyone to edit ...
research
∙
06/03/2017