A Novel Autonomous Perceptron Model for Pattern Classification Applications
TLDR
A novel autonomous perceptron model (APM) that can solve the problem of the architecture complexity of traditional ANNs is proposed, which has a simple and fixed architecture inspired by the computational superposition power of the qubit.Abstract:
Pattern classification represents a challenging problem in machine learning and data science research domains, especially when there is a limited availability of training samples. In recent years, artificial neural network (ANN) algorithms have demonstrated astonishing performance when compared to traditional generative and discriminative classification algorithms. However, due to the complexity of classical ANN architectures, ANNs are sometimes incapable of providing efficient solutions when addressing complex distribution problems. Motivated by the mathematical definition of a quantum bit (qubit), we propose a novel autonomous perceptron model (APM) that can solve the problem of the architecture complexity of traditional ANNs. APM is a nonlinear classification model that has a simple and fixed architecture inspired by the computational superposition power of the qubit. The proposed perceptron is able to construct the activation operators autonomously after a limited number of iterations. Several experiments using various datasets are conducted, where all the empirical results show the superiority of the proposed model as a classifier in terms of accuracy and computational time when it is compared with baseline classification models.read more
Citations
More filters
Journal ArticleDOI
Scene Semantic Recognition Based on Modified Fuzzy C-Mean and Maximum Entropy Using Object-to-Object Relations
TL;DR: Zhang et al. as discussed by the authors proposed a novel scene semantic recognition (SSR) framework that intelligently segments the locations of objects, generates a novel Bag of Features, and recognizes scenes via Maximum Entropy.
Journal ArticleDOI
Improving the Accuracy for Analyzing Heart Diseases Prediction Based on the Ensemble Method
TL;DR: In this article, bagging ensemble learning method with decision tree has achieved the best performance in predicting heart disease, which is the deadliest disease and one of leading causes of death worldwide.
Posted Content
Classification with Quantum Machine Learning: A Survey.
TL;DR: This paper presents and summarizes a comprehensive survey of the state-of-the-art advances in Quantum Machine Learning (QML), and proposes a classification scheme in the quantum world and discusses encoding methods for mapping classical data to quantum data.
Journal ArticleDOI
A quantum classification algorithm for classification incomplete patterns based on entanglement measure
Abdel-Haleem Abdel-Aty,Heba Kadry,Mohammed Zidan,Yazeed Al-Sbou,E. A. Zanaty,Mahmoud Abdel-Aty +5 more
Book ChapterDOI
Quantum Machine Learning: A Review and Current Status
Nimish Mishra,Manik Kapil,Hemant Rakesh,Amit Anand,Nilima Mishra,Aakash Warke,Soumya Sarkar,Sanchayan Dutta,Sabhyata Gupta,Aditya Prasad Dash,Rakshit Gharat,Yagnik Chatterjee,Shuvarati Roy,Shivam Raj,Valay Kumar Jain,Shreeram Bagaria,Smit Chaudhary,Vishwanath Singh,Rituparna Maji,Priyanka Dalei,Bikash K. Behera,Sabyasachi Mukhopadhyay,Prasanta K. Panigrahi +22 more
TL;DR: The previous literature on quantum machine learning is reviewed and the current status of it is provided, postulating that quantum computers may overtake classical computers on machine learning tasks.
References
More filters
Book
The Nature of Statistical Learning Theory
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
Book
Quantum Computation and Quantum Information
TL;DR: In this article, the quantum Fourier transform and its application in quantum information theory is discussed, and distance measures for quantum information are defined. And quantum error-correction and entropy and information are discussed.
Journal ArticleDOI
Quantum computation and quantum information
TL;DR: This special issue of Mathematical Structures in Computer Science contains several contributions related to the modern field of Quantum Information and Quantum Computing, with a focus on entanglement.
Book
Topics in Matrix Analysis
TL;DR: The field of values as discussed by the authors is a generalization of the field of value of matrices and functions, and it includes singular value inequalities, matrix equations and Kronecker products, and Hadamard products.
Proceedings ArticleDOI
A fast quantum mechanical algorithm for database search
TL;DR: In this paper, it was shown that a quantum mechanical computer can solve integer factorization problem in a finite power of O(log n) time, where n is the number of elements in a given integer.