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Support Vector Machines with Quantum State Discrimination
We analyze possible connections between quantum-inspired classifications and support vector machines. Quantum state discrimination and optimal quantum measurement are useful tools for classification problems. In order to use these tools, feature vectors have to be encoded in quantum states represented by density operators. Classification algorithms inspired by quantum state discrimination and implemented on classic computers have been recently proposed. We focus on the implementation of a knowndoi:10.3390/quantum3030032 fatcat:ex2cqgnxdnathgdoyle7jwre3u