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Found 6 papers, 0 papers with code
Investigation into the Potential of Parallel Quantum Annealing for Simultaneous Optimization of Multiple Problems: A Comprehensive Study
Parallel Quantum Annealing is a technique to solve multiple optimization problems simultaneously.
Parts of Speech Tagging in NLP: Runtime Optimization with Quantum Formulation and ZX Calculus
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).
An Investigation of Quantum Deep Clustering Framework with Quantum Deep SVM & Convolutional Neural Network Feature Extractor
We have investigated the run time computational complexity of the proposed quantum deep clustering framework and compared with the possible classical implementation.
An Investigation on Support Vector Clustering for Big Data in Quantum Paradigm
In this paper, we have investigated the performance of support vector clustering algorithm implemented in a quantum paradigm for possible run-time improvements.
Gaussian Kernel in Quantum Learning
The Gaussian kernel is a very popular kernel function used in many machine learning algorithms, especially in support vector machines (SVMs).
An All-Pair Quantum SVM Approach for Big Data Multiclass Classification
We have shown that the multiclass support vector machine for big data classification with a quantum all-pair approach can be implemented in logarithm runtime complexity on a quantum computer.
