Search Results for author:
Found 3 papers, 0 papers with code
Theory and Practice of Quality Assurance for Machine Learning Systems An Experiment Driven Approach
The crafting of machine learning (ML) based systems requires statistical control throughout its life cycle.
Broadly Applicable Targeted Data Sample Omission Attacks
We show that, with a low attack budget, our attack's success rate is above 80%, and in some cases 100%, for white-box learning.
Defending via strategic ML selection
There are cases in which an adversary can strategically tamper with the input data to affect the outcome of the learning process.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
