Learning quantum operator by quantum adiabatic computation
2014
In this article, we introduce the quantum adiabatic computation to the research field of quantum operator learning. Compared with existing conventional optimization approaches, the adiabatic algorithm ensures to reach the global optimal solution, and thus avoids the local minimum problem. The performance of the experiments on two tasks indicates the feasibility and potentiality of this novel method. We firmly believe that the quantum adiabatic computation can be applied to other tasks of machine learning.
Keywords:
- Quantum error correction
- Adiabatic quantum computation
- Mathematical optimization
- Quantum phase estimation algorithm
- Quantum operation
- Quantum capacity
- Quantum algorithm
- Mathematics
- Quantum computer
- Open quantum system
- Quantum network
- Computer vision
- Algorithm
- Quantum process
- Computer science
- Artificial intelligence
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