2 papers
cs.LG2026
Model Stealing Through the Lens of Model Multiplicity
Eliott Baltz, Satoshi Hara, Ulrich Aïvodji
Model stealing attacks, where adversaries create high-fidelity surrogate models, are a significant threat to the intellectual property of machine learning services. Conventional wi…
cs.LG2025
Data Cleansing for GANs
Naoyuki Terashita, Hiroki Ohashi, Satoshi Hara
As the application of generative adversarial networks (GANs) expands, it becomes increasingly critical to develop a unified approach that improves performance across various genera…