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Efficient Quantum Circuits for Machine Learning Activation Functions including Constant T-depth ReLU
In recent years, Quantum Machine Learning (QML) has increasingly captured the interest of researchers.
Adversarial Attacks and Dimensionality in Text Classifiers
For all of the aforementioned studies, we have run tests on multiple models with varying dimensionality and used a word-vector level adversarial attack to substantiate the findings.
Privacy and Security Implications of Cloud-Based AI Services : A Survey
This paper details the privacy and security landscape in today's cloud ecosystem and identifies that there is a gap in addressing the risks introduced by machine learning models.
Spatially Correlated Patterns in Adversarial Images
Adversarial attacks have proved to be the major impediment in the progress on research towards reliable machine learning solutions.
Adversarial Attacks and Defences: A Survey
Deep learning has emerged as a strong and efficient framework that can be applied to a broad spectrum of complex learning problems which were difficult to solve using the traditional machine learning techniques in the past.
