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Quantum Optimization
Quantum Machine Learning
Parts of Speech Tagging in NLP: Runtime Optimization with Quantum Formulation and ZX Calculus
arXiv
Authors: Arit Kumar Bishwas, Ashish Mani, Vasile Palade
Year
2020
Paper ID
22123
Status
Preprint
Abstract Read
~2 min
Abstract Words
69
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Abstract
This paper proposes an optimized formulation of the parts of speech tagging in Natural Language Processing with a quantum computing approach and further demonstrates the quantum gate-level runnable optimization with ZX-calculus, keeping the implementation target in the context of Noisy Intermediate Scale Quantum Systems (NISQ). Our quantum formulation exhibits quadratic speed up over the classical counterpart and further demonstrates the implementable optimization with the help of ZX calculus postulates.
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- This paper proposes an optimized formulation of the parts of speech tagging in Natural Language Processing with a quantum computing approach and further demonstrates the...
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