Maya Fuchs

Publication Activity (10 Years)

Years Active: 2022-2024
Publications (10 Years): 6

Top Topics

Differential Privacy

Training Dataset

Differentially Private

Top Venues

Publications

Chang Liu, Rebecca Saul, Yihao Sun, Edward Raff, Maya Fuchs, Townsend Southard Pantano, James Holt, Kristopher K. Micinski
Assemblage: Automatic Binary Dataset Construction for Machine Learning. CoRR (2024)
Tyler LeBlond, Joseph Munoz, Fred Lu, Maya Fuchs, Elliott Zaresky-Williams, Edward Raff, Brian Testa
Probing the Transition to Dataset-Level Privacy in ML Models Using an Output-Specific and Data-Resolved Privacy Profile. CoRR (2023)
Tyler LeBlond, Joseph Munoz, Fred Lu, Maya Fuchs, Elliott Zaresky-Williams, Edward Raff, Brian Testa
Probing the Transition to Dataset-Level Privacy in ML Models Using an Output-Specific and Data-Resolved Privacy Profile. AISec@CCS (2023)
Fred Lu, Joseph Munoz, Maya Fuchs, Tyler LeBlond, Elliott Zaresky-Williams, Edward Raff, Francis Ferraro, Brian Testa
A General Framework for Auditing Differentially Private Machine Learning. CoRR (2022)
André T. Nguyen, Richard Zak, Luke E. Richards, Maya Fuchs, Fred Lu, Robert Brandon, Gary Lopez Munoz, Edward Raff, Charles Nicholas, James Holt
Minimizing Compute Costs: When Should We Run More Expensive Malware Analysis? CAMLIS (2022)
Fred Lu, Joseph Munoz, Maya Fuchs, Tyler LeBlond, Elliott Zaresky-Williams, Edward Raff, Francis Ferraro, Brian Testa
A General Framework for Auditing Differentially Private Machine Learning. NeurIPS (2022)