[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121049-en":3,"doc-seo-121049-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},121049,2336464648322,"Aria","https://ap-avatar.wpscdn.com/avatar/2200025388227c56fec?_k=1778556882303663488",8,"Research & Report","Evaluating the Role of Quantum Algorithms in Supervised Machine Learning - A Thesis","This thesis evaluates how quantum algorithms can contribute to supervised machine learning, focusing on where quantum methods may provide enhancements over classical approaches. It reviews prior work on quantum enhancement for both supervised and unsupervised learning and consolidates key building blocks needed for quantum machine learning. Core concepts include linear algebra, quantum physics foundations such as bra-ket notation and entanglement, and practical quantum programming with Qiskit, including quantum gates and qubit operations.","UNIVERSITY OF OKLAHOMA  \nGRADUATE COLLEGE  \nEVALUATING THE ROLE OF QUANTUM ALGORITHMS IN SUPERVISED MACHINE LEARNING  \nA THESIS  \nSUBMITTED TO THE GRADUATE FACULTY in partial fulfillment of the requirements for the Degree of  \nMASTER OF SCIENCE  \nBy  \nPABLO GUTIÉRREZ FÉLIX Norman, Oklahoma  \nEVALUATING THE ROLE OF QUANTUM ALGORITHMS IN  \nSUPERVISED MACHINE LEARNING  \nA THESIS APPROVED FOR THE  \nMICHAEL F. PRICE COLLEGE OF BUSINESS  \nBY THE COMMITTEE CONSISTING OF  \nDr. Naveen Kumar, Chair Dr. Radhika Santhanam  \nDr. Rajendra Singh  \n© Copyright by PABLO GUTÉRREZ FÉLIX 2024  \nAll Rights Reserved.  \nTable of Contents  \nChapter 1: Introduction  \n1.1 Background ............................................................................................................................... 1  \n1.2 Objectives and Research Question............................................................................................ 4  \n1.3 Key Contributions ..................................................................................................................... 5  \nChapter 2: Literature Review  \n2.1 Quantum Enhancement in Supervised Learning....................................................................... 7  \n2.2 Quantum Enhancement in Unsupervised Learning ................................................................ 10  \n2.3 Summary ................................................................................................................................. 11  \nChapter 3: Building Blocks of Quantum Machine Learning  \n3.1 Linear Algebra ........................................................................................................................ 13  \n3.1.1 Vectors ............................................................................................................................. 13  \n3.1.1.1 Vector Addition ......................................................................................................... 15  \n3.1.1.2 Vector Multiplication ................................................................................................ 15  \n3.1.1.3 Vectors in Quantum Computing................................................................................ 17  \n3.1.2 Linear Independence and Vector Basis ............................................................................ 18  \n3.1.2.1 Vector Basis in Quantum Computing........................................................................ 20  \n3.1.3 Linear Transformations .................................................................................................... 21  \n3.1.4 Matrixes............................................................................................................................ 24  \n3.1.4.1 Matrixes in Quantum Computing .............................................................................. 26  \n3.1.5 Dot Product ...................................................................................................................... 26  \n3.1.5.1 Dot Product in Quantum Computing......................................................................... 28  \n3.1.6 Eigenvectors and Eigenvalues .......................................................................................... 29  \n3.1.6.1 Eigenvectors and Eigenvalues in Quantum Computing ............................................ 32  \n3.1.7 Summary .......................................................................................................................... 32  \n3.2 Quantum Physics .................................................................................................................... 33  \n3.2.1 The Language of Quantum Mechanics ............................................................................ 33  \n3.2.2 Bra-ket Notation ............................................................................................................... 36  \n3.2.3 Entanglement.............................................................","cbCaih9If0RECHvD","https://ap.wps.com/l/cbCaih9If0RECHvD","pdf",7183571,1,106,"English","en",105,"# Chapter 1: Introduction\n## 1.1 Background\n## 1.2 Objectives and Research Question\n## 1.3 Key Contributions\n# Chapter 2: Literature Review\n## 2.1 Quantum Enhancement in Supervised Learning\n## 2.2 Quantum Enhancement in Unsupervised Learning\n## 2.3 Summary\n# Chapter 3: Building Blocks of Quantum Machine Learning\n## 3.1 Linear Algebra\n## 3.2 Quantum Physics\n## 3.3 Quantum Programming with Qiskit","[{\"question\":\"What is the main objective of the thesis?\",\"answer\":\"The thesis aims to evaluate the role of quantum algorithms in supervised machine learning, including the research question and intended contributions.\"},{\"question\":\"How does the thesis approach existing research?\",\"answer\":\"It provides a literature review covering quantum enhancement in supervised learning and also in unsupervised learning, followed by a summary.\"},{\"question\":\"What technical foundations are covered for quantum machine learning?\",\"answer\":\"It covers linear algebra and quantum physics concepts, then discusses quantum programming with Qiskit, including quantum gates and qubit entanglement operations.\"}]","Evaluating the Role of Quantum Algorithms in Supervised Machine Learning - 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