DQMW-Sample realizes a classically hard online learning primitive via dissipative quantum dynamics with sublinear regret and proven hardness for classical simulation including PH collapse.
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A survey of quantum adversarial machine learning covering attacks, countermeasures, theoretical underpinnings, trends, and challenges.
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Dissipative Quantum Multiplicative Weights with Sampling Feedback: A Classically Hard Primitive Realized via Engineered Open-System Dynamics
DQMW-Sample realizes a classically hard online learning primitive via dissipative quantum dynamics with sublinear regret and proven hardness for classical simulation including PH collapse.
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Quantum Adversarial Machine Learning: From Classical Adaptations to Quantum-Native Methods
A survey of quantum adversarial machine learning covering attacks, countermeasures, theoretical underpinnings, trends, and challenges.