Yi Zeng

DeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation

2021

Public resources and services (e.g., datasets, training platforms, pre-trained models) have been widely adopted to ease the development of Deep Learning-based applications. However, if the third-party providers are untrusted, they can inject poisoned samples into …

Fine-tuning Is Not Enough: A Simple yet Effective Watermark Removal Attack for DNN Models

2021

Watermarking has become the tendency in protecting the intellectual property of DNN models. Recent works, from the adversary's perspective, attempted to subvert watermarking mechanisms by designing watermark removal attacks. However, these attacks mainly adopted sophisticated …

LAVA: Data Valuation without Pre-Specified Learning Algorithms

2023 · arXiv (Cornell University)

Traditionally, data valuation (DV) is posed as a problem of equitably splitting the validation performance of a learning algorithm among the training data. As a result, the calculated data values depend on many design choices …