Quantum Machine Learning: Exploring the Future of AI with Quantum Computing
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Abstract
Quantum computing has the potential to revolutionize machine learning by exponentially increasing computational power. This paper provides an overview of quantum machine learning (QML) algorithms, including quantum support vector machines and variational quantum circuits. A comparative analysis of classical and quantum models is conducted, demonstrating QML’s advantages in solving complex optimization problems. While still in its early stages, the research suggests that QML could unlock new frontiers in AI, paving the way for faster and more efficient computations.
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References
Maturi, M. H., Gonaygunta, H., Nadella, G. S., & Meduri, K. (2023). Fault Diagnosis and Prognosis using IoT in Industry 5.0. International Numeric Journal of Machine Learning and Robots, 7(7), 1-21. https://injmr.com/index.php/fewfewf/article/view/80
Satish, S., Meduri, K., Nadella, G. S., & Gonaygunta , H. (2022). Developing a Decentralized AI Model Training Framework Using Blockchain Technology. International Meridian Journal, 4(4), 1-20. https://meridianjournal.in/index.php/IMJ/article/view/71
Balantrapu, S. S. (2021). The Impact of Machine Learning on Incident Response Strategies. International Journal of Management Education for Sustainable Development, 4(4), 1-17.
Nadella, G., Meduri, S., Gonaygunta, H., & Podicheti, S. (2023). Understanding the Role of Social Influence on Consumer Trust in Adopting AI Tools. International Journal of Sustainable Development in Computing Science, 5(2), 1-18. Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/516
The Intersection of Artificial Intelligence and Neuroscience: Unlocking the Mysteries of the Brain (M. H. Maturi, S. Satish, H. Gonaygunta, & K. Meduri , Trans.). (2022). International Journal of Creative Research In Computer Technology and Design, 4(4), 1-21. https://jrctd.in/index.php/IJRCTD/article/view/65
Meduri, K., Nadella, G., Gonaygunta, H., & Meduri, S. (2023). Developing a Fog Computing-based AI Framework for Real-time Traffic Management and Optimization. International Journal of Sustainable Development in Computing Science, 5(4), 1-24. Retrieved from https://ijsdcs.com/index.php/ijsdcs/article/view/517
Gonaygunta, H., Meduri, S., Podicheti, S., & Nadella, G. (2023). The Impact of Virtual Reality on Social Interaction and Relationship via Statistical Analysis. International Journal of Machine Learning for Sustainable Development, 5(2), 1-20. Retrieved from https://ijsdcs.com/index.php/IJMLSD/article/view/518
Nadella, G., Gonaygunta, H., Meduri, K., & Satish, S. (2023). Adversarial Attacks on Deep Neural Network: Developing Robust Models Against Evasion Technique. Transactions on Latest Trends in Artificial Intelligence, 4(4). Retrieved from https://ijsdcs.com/index.php/TLAI/article/view/515
Balantrapu, S. S. (2021). The Impact of Machine Learning on Incident Response Strategies. International Journal of Management Education for Sustainable Development, 4(4), 1-17.
Balantrapu, S. S. (2022). Ethical Considerations in AI-Powered Cybersecurity. International Machine learning journal and Computer Engineering, 5(5).
Balantrapu, S. S. (2019). Adversarial Machine Learning: Security Threats and Mitigations. International Journal of Sustainable Development in Computing Science, 1(3), 1-18.
Balantrapu, S. S. (2022). Evaluating AI-Enhanced Cybersecurity Solutions Versus Traditional Methods: A Comparative Study. International Journal of Sustainable Development Through AI, ML and IoT, 1(1), 1-15.
Balantrapu, S. S. (2020). AI-Driven Cybersecurity Solutions: Case Studies and Applications. International Journal of Creative Research In Computer Technology and Design, 2(2).
Balantrapu, S. S. (2021). A systematic review comparative analysis of machine learning algorithms for malware classification. International Scientific Journal for Research, 3(3), 1-29.
Balantrapu, S. S. (2023). Cybersecurity Frameworks Enhanced by Machine Learning Techniques. International Journal of Sustainable Development in Computing Science, 5(4), 1-19.
Balantrapu, S. S. (2023). Evaluating the effectiveness of machine learning in phishing detection. International Scientific Journal for Research, 5(5).
Banerjee, S., & Parisa, S. K. (2023). AI-Powered Blockchain for Securing Retail Supply Chains in Multi-Cloud Environments. International Journal of Sustainable Development in computer Science Engineering, 9(9).
Banerjee, S., & Parisa, S. K. (2023). AI-Enhanced Intrusion Detection Systems for Retail Cloud Networks: A Comparative Analysis. Transactions on Recent Developments in Artificial Intelligence and Machine Learning, 15(15).
Parisa, S. K., Banerjee, S., & Whig, P. (2023). AI-Driven Zero Trust Security Models for Retail Cloud Infrastructure: A Next-Generation Approach. International Journal of Sustainable Devlopment in field of IT, 15(15).
Banerjee, S. (2023). Challenges and Solutions for Data Management in Cloud-Based Environments. International Journal of Advanced Research in Science, Communication and Technology, 370-378.