1 citations · 1 across the 4 of their papers we have counts for
5 papers
IDSPACE: A Novel Document Generator for Reliable Evaluation of Digital Identity Verification Systems [Extended Technical Report]
Lulu Xie, Yancheng Wang, Kanchan Chowdhury +3
As services move online, trust institutions such as banks, lenders, and governments must verify the identity of remote users. Fraud detection tools are widely available, but evalua…
CACTUSDB: Unlock Co-Optimization Opportunities for SQL and AI/ML Inferences
Lixi Zhou, Kanchan Chowdhury, Lulu Xie +5
There is a growing demand for supporting inference queries that combine Structured Query Language (SQL) and Artificial Intelligence / Machine Learning (AI/ML) model inferences in d…
InferF: Declarative Factorization of AI/ML Inferences over Joins
Kanchan Chowdhury, Lixi Zhou, Lulu Xie +2
Real-world AI/ML workflows often apply inference computations to feature vectors joined from multiple datasets. To avoid the redundant AI/ML computations caused by repeated data re…
Privacy and Accuracy-Aware AI/ML Model Deduplication
Hong Guan, Lei Yu, Lixi Zhou +5
With the growing adoption of privacy-preserving machine learning algorithms, such as Differentially Private Stochastic Gradient Descent (DP-SGD), training or fine-tuning models on…
IDNet: A Novel Dataset for Identity Document Analysis and Fraud Detection
Hong Guan, Yancheng Wang, Lulu Xie +8
Effective fraud detection and analysis of government-issued identity documents, such as passports, driver's licenses, and identity cards, are essential in thwarting identity theft…