4 citations · 10 across the 5 of their papers we have counts for
5 papers
Privacy-Preserving Debiasing using Data Augmentation and Machine Unlearning
Zhixin Pan, Emma Andrews, Laura Chang +1
Data augmentation is widely used to mitigate data bias in the training dataset. However, data augmentation exposes machine learning models to privacy attacks, such as membership in…
Hardware Acceleration of Explainable Artificial Intelligence
Zhixin Pan, Prabhat Mishra
Machine learning (ML) is successful in achieving human-level artificial intelligence in various fields. However, it lacks the ability to explain an outcome due to its black-box nat…
Backdoor Attacks on Bayesian Neural Networks using Reverse Distribution
Zhixin Pan, Prabhat Mishra
Due to cost and time-to-market constraints, many industries outsource the training process of machine learning models (ML) to third-party cloud service providers, popularly known a…
Fast Approximate Spectral Normalization for Robust Deep Neural Networks
Zhixin Pan, Prabhat Mishra
Deep neural networks (DNNs) play an important role in machine learning due to its outstanding performance compared to other alternatives. However, DNNs are not suitable for safety-…
Hardware Acceleration of Explainable Machine Learning using Tensor Processing Units
Zhixin Pan, Prabhat Mishra
Machine learning (ML) is successful in achieving human-level performance in various fields. However, it lacks the ability to explain an outcome due to its black-box nature. While e…