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Found 5 papers, 1 papers with code
Collective optimization for variational quantum eigensolvers
Variational quantum eigensolver (VQE) optimizes parameterized eigenstates of a Hamiltonian on a quantum processor by updating parameters with a classical computer.
Quantum Physics
Quantum-enhanced least-square support vector machine: simplified quantum algorithm and sparse solutions
We also incorporate kernel methods into the above quantum algorithms, which uses both exponential growth Hilbert space of qubits and infinite dimensionality of continuous variable for quantum feature maps.
Protocol for implementing quantum nonparametric learning with trapped ions
A quantum training state is introduced to superpose all data of samples, encoding relevant information for learning in its bipartite entanglement spectrum.
Nonlinear regression based on a hybrid quantum computer
Incorporating nonlinearity into quantum machine learning is essential for learning a complicated input-output mapping.
Realizing quantum linear regression with auxiliary qumodes
In order to exploit quantum advantages, quantum algorithms are indispensable for operating machine learning with quantum computers.
