Local LMO is a new projection-free method that achieves the convergence rates of projected gradient descent for constrained optimization by using local linear minimization oracles over small balls.
Advances in Neural Information Processing Systems , volume=
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A variational quantum classifier with normalized amplitude embeddings and bounded observables achieves competitive accuracy with improved robustness and stability over classical baselines in safety-critical settings.
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Local LMO: Constrained Gradient Optimization via a Local Linear Minimization Oracle
Local LMO is a new projection-free method that achieves the convergence rates of projected gradient descent for constrained optimization by using local linear minimization oracles over small balls.
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SAFE Quantum Machine Learning with Variational Quantum Classifiers
A variational quantum classifier with normalized amplitude embeddings and bounded observables achieves competitive accuracy with improved robustness and stability over classical baselines in safety-critical settings.