Quantum Computational Intelligence for Massive Data

Recently, an increasing interest of the scientific community has been directed towards the issues of quantum computing, a discipline that is attracting the attention of many government bodies and large international companies for its significant application developments and their impact on future society. In particular, quantum computational intelligence represents one of the emerging issues for potential applications in the near future to significantly increase the performances of classical algorithms for artificial intelligence, especially in the presence of high dimensional, large-scale and massive data, which are needed today in numerous industrial applications and real-world issues. This special issue is aimed at researchers proposing new quantum computational intelligence methods or experimenting with quantum-inspired computational intelligence methods on classical machines, in applications where high-dimensional massive data must be used to represent and manage the real world and the use of traditional computational intelligence algorithms is unsuitable or provides poor performance results. We hope that this special issue will attract numerous researchers who will help provide an update on the latest developments in the field of quantum computational intelligence techniques in the presence of massive data and their important applications in complex realworld problems Topics covered are: - Quantum algorithms for machine learning tasks - Quantum and quantum inspired clustering of massive data - Quantum and quantum inspired classification and regression of massive data - Quantum big data analytics - Quantum techniques for social media data mining - Quantum support vector machines - Fuzzy reasoning and uncertainty in quantum computation - Quantum-inspired evolutionary computation for big data analytics - Quantum neural networks