Copertina

VecAug: Unveiling Camouflaged Frauds with Cohort Augmentation for Enhanced Detection

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Xiao, Fei, Cai, Shaofeng, Chen, Gang, Jagadish, H. V., Ooi, Beng Chin, Zhang, Meihui
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

CohortNet: Empowering Cohort Discovery for Interpretable Healthcare Analytics
di: Cai, Qingpeng, et al.
Pubblicazione: (2024)

METER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection
di: Zhu, Jiaqi, et al.
Pubblicazione: (2023)

Catching Every Ripple: Enhanced Anomaly Awareness via Dynamic Concept Adaptation
di: Zhu, Jiaqi, et al.
Pubblicazione: (2026)

Anytime Neural Architecture Search on Tabular Data
di: Xing, Naili, et al.
Pubblicazione: (2024)

NeurDB: On the Design and Implementation of an AI-powered Autonomous Database
di: Zhao, Zhanhao, et al.
Pubblicazione: (2024)

NeurDB: An AI-powered Autonomous Data System
di: Ooi, Beng Chin, et al.
Pubblicazione: (2024)

HAKES: Scalable Vector Database for Embedding Search Service
di: Hu, Guoyu, et al.
Pubblicazione: (2025)

SCFCRC: Simultaneously Counteract Feature Camouflage and Relation Camouflage for Fraud Detection
di: Zhang, Xiaocheng, et al.
Pubblicazione: (2025)

Do LLMs Understand Visual Anomalies? Uncovering LLM's Capabilities in Zero-shot Anomaly Detection
di: Zhu, Jiaqi, et al.
Pubblicazione: (2024)

Toward Robust Signed Graph Learning through Joint Input-Target Denoising
di: Wu, Junran, et al.
Pubblicazione: (2025)

From Schema to Signal: Retrieval-Augmented Modeling for Relational Data Analytics
di: Zeng, Lingze, et al.
Pubblicazione: (2026)

In-Context Adaptation to Concept Drift for Learned Database Operations
di: Zhu, Jiaqi, et al.
Pubblicazione: (2025)

Exploring Privacy and Fairness Risks in Sharing Diffusion Models: An Adversarial Perspective
di: Luo, Xinjian, et al.
Pubblicazione: (2024)

Towards Effective Orchestration of AI x DB Workloads
di: Xing, Naili, et al.
Pubblicazione: (2026)

Powering In-Database Dynamic Model Slicing for Structured Data Analytics
di: Zeng, Lingze, et al.
Pubblicazione: (2024)

NeurIDA: Dynamic Modeling for Effective In-Database Analytics
di: Zeng, Lingze, et al.
Pubblicazione: (2025)

Distribution-aware Online Continual Learning for Urban Spatio-Temporal Forecasting
di: Wang, Chengxin, et al.
Pubblicazione: (2024)

NeurStore: Efficient In-database Deep Learning Model Management System
di: Xiang, Siqi, et al.
Pubblicazione: (2025)

CAMERA: Adapting to Semantic Camouflage in Unsupervised Text-Attributed Graph Fraud Detection
di: Pan, Junjun, et al.
Pubblicazione: (2026)

Passive Inference Attacks on Split Learning via Adversarial Regularization
di: Zhu, Xiaochen, et al.
Pubblicazione: (2023)

NeurBench: A Benchmark Suite for Learned Database Components with Drift Modeling
di: Zhao, Zhanhao, et al.
Pubblicazione: (2025)

Chameleon: Foundation Models for Fairness-aware Multi-modal Data Augmentation to Enhance Coverage of Minorities
di: Erfanian, Mahdi, et al.
Pubblicazione: (2024)

Modeling Concurrency Control as a Learnable Function
di: Pan, Hexiang, et al.
Pubblicazione: (2025)

NL2SQLBench: A Modular Benchmarking Framework for LLM-Enabled NL2SQL Solutions
di: Hou, Shizheng, et al.
Pubblicazione: (2026)

Teaching Wav2Vec2 the Language of the Brain
di: Fiedler, Tobias, et al.
Pubblicazione: (2025)

Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy
di: Bao, Ergute, et al.
Pubblicazione: (2022)

Camouflaged Image Synthesis Is All You Need to Boost Camouflaged Detection
di: Zhang, Haichao, et al.
Pubblicazione: (2023)

FraudTransformer: Time-Aware GPT for Transaction Fraud Detection
di: Aminian, Gholamali, et al.
Pubblicazione: (2025)

FraudFox: Adaptable Fraud Detection in the Real World
di: Butler, Matthew, et al.
Pubblicazione: (2026)

SeSeMI: Secure Serverless Model Inference on Sensitive Data
di: Hu, Guoyu, et al.
Pubblicazione: (2024)

CGCOD: Class-Guided Camouflaged Object Detection
di: Zhang, Chenxi, et al.
Pubblicazione: (2024)

SilIF: Silhouette-Augmented Isolation Forest for Unsupervised Transaction Fraud Detection
di: Gopalakrishnan, Venkatakrishnan
Pubblicazione: (2026)

Enhancing Ethereum Fraud Detection via Generative and Contrastive Self-supervision
di: Jin, Chenxiang, et al.
Pubblicazione: (2024)

Improving log-based anomaly detection through learned adaptive filter
di: Xiong, Yiyuan, et al.
Pubblicazione: (2025)

Enhancing Customer Contact Efficiency with Graph Neural Networks in Credit Card Fraud Detection Workflow
di: Huo, Menghao, et al.
Pubblicazione: (2025)

FracAug: Fractional Augmentation boost Graph-level Anomaly Detection under Limited Supervision
di: Dong, Xiangyu, et al.
Pubblicazione: (2025)

Grad: Guided Relation Diffusion Generation for Graph Augmentation in Graph Fraud Detection
di: Yang, Jie, et al.
Pubblicazione: (2025)

DGP: A Dual-Granularity Prompting Framework for Fraud Detection with Graph-Enhanced LLMs
di: Li, Yuan, et al.
Pubblicazione: (2025)

Improving Credit Card Fraud Detection through Transformer-Enhanced GAN Oversampling
di: Emaan, Kashaf Ul
Pubblicazione: (2025)

Credit Card Fraud Detection
di: Popova, Iva, et al.
Pubblicazione: (2025)