aqora

A Quantum-inspired Approach to Pattern Recognition and Machine Learning. Part I

María Luisa Dalla Chiara, Roberto Giuntini, Giuseppe Sergioli

International Journal of Theoretical PhysicsFeb 21, 20240 citations

Revolutionizing Pattern Recognition with Quantum Machine Learning

K. P. Uma, T. Gopu

Information systems engineering and managementJan 1, 20250 citations

Improved Pattern Recognition—Quantum Machine Learning

Siya Khanna, Shruti Dhingra, Nidhi Sindhwani +1 more

Information systems engineering and managementJan 1, 20250 citations

Quantum machine learning for supervised pattern recognition.

Maria Schuld

Humans are experts at recognising patterns in past experience and applying them to new tasks.For example, after seeing pictures of a face we can usually tell if another image contains the same person or not.Machine learning is a research discipline at the intersection of computer science, statistics and mathematics that investigates how pattern recognition can be performed by machines and for large amounts of data.Since a few years machine learning has come

Jan 1, 20175 citations

Quantum Machine Learning Pattern Recognition

Jincheng Zhang

Quantum Machine Learning Pattern Recognition explores the potential of quantum algorithms to revolutionize pattern recognition, particularly in the context of high-dimensional data. This paper introduces a novel approach utilizing quantum machine learning principles to enhance model accuracy and robustness, addressing limitations inherent in traditional machine learning methods. We detail the core mechanism—a hybrid quantum-classical approach—that leverages quantum feature extraction and parallel processing to overcome challenges associated with high-dimensional data, offering a paradigm shift in pattern identification. The core claim is that this method surpasses traditional approaches in handling complex, high-dimensional datasets, exhibiting enhanced generalization capabilities and a deeper understanding of underlying patterns. We provide a conceptual framework and preliminary results demonstrating the effectiveness of this approach, highlighting its potential impact across various domains.Quantum Machine Learning Pattern Recognition explores the potential of quantum algorithms to revolutionize pattern recognition, particularly in the context of high-dimensional data. This paper introduces a novel approach utilizing quantum machine learning principles to enhance model accuracy and robustness, addressing limitations inherent in traditional machine learning methods. We detail the core mechanism—a hybrid quantum-classical approach—that leverages quantum feature extraction and parallel processing to overcome challenges associated with high-dimensional data, offering a paradigm shift in pattern identification. The core claim is that this method surpasses traditional approaches in handling complex, high-dimensional datasets, exhibiting enhanced generalization capabilities and a deeper understanding of underlying patterns. We provide a conceptual framework and preliminary results demonstrating the effectiveness of this approach, highlighting its potential impact across various domains.

Sep 5, 20260 citations

Quantum Machine Learning: A Primer

Madhusudan Singh Irish Singh, Bharat S. Rawal

Springer eBooksJan 1, 20260 citations

A Quantum Approach to Pattern Recognition and Machine Learning. Part II

Related papers

A Quantum Approach to Pattern Recognition and Machine Learning. Part II

Related papers