[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122851-en":3,"doc-seo-122851-105":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},122851,4810365810221,"Aurora","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Machine Learning Methods for Stochastic Differential Games and those with Delay: Applications and Modeling in Epidemiology and Finance - Thesis summary","Machine learning methods for stochastic differential games with delay are developed to support modeling of complex, real-world systems. The dissertation focuses on finding Nash equilibria in delayed stochastic differential games to improve predictive power for scientists and practitioners. Applications are targeted to epidemiology and finance, including COVID-19 dynamics and policy modeling, as well as competitive portfolio allocation under market features such as taxes. Research achievements include new machine learning methodologies for solving delayed stochastic differential games and constructing corresponding financial models.","UC Santa Barbara  \nUC Santa Barbara Electronic Theses and Dissertations  \nTitle  \nMachine Learning Methods for Stochastic Differential Games and those with Delay: Applications and Modeling in Epidemiology and Finance  \nPermalink  \n[https://escholarship.org/uc/item/602077fg](https://escholarship.org/uc/item/602077fg)  \nAuthor  \nBalkin, Robert Andrew  \nPublication Date  \n2023  \nPeer reviewed|Thesis/dissertation  \n[eScholarship.org](eScholarship.org) Powered by the California Digital Library  \nUniversity of California  \nUniversity of California  \nSanta Barbara  \nMachine Learning Methods for Stochastic Differential Games and those with Delay: Applications and Modeling in Epidemiology and Finance  \nA dissertation submitted in partial satisfaction of the requirements for the degree  \nDoctor of Philosophy  \nin  \nMathematics  \nby  \nRobert Andrew Balkin  \nCommittee in charge:  \nProfessor Hector D. Ceniceros, Co-Chair  \nProfessor Ruimeng Hu, Co-Chair  \nProfessor Carlos Garcia-Cervera  \nSeptember 2023  \nThe dissertation of Robert Andrew Balkin is approved.  \nProfessor Carlos Garcia-Cervera  \nProfessor Hector D. Ceniceros, Co-Chair  \nProfessor Ruimeng Hu, Co-Chair  \nSeptember 2023  \nMachine Learning Methods for Stochastic Differential Games and those with Delay: Applications and Modeling in Epidemiology and Finance  \nCopyright © 2023  \nby  \nRobert Andrew Balkin  \nAcknowledgements  \nI am exceedingly grateful to my advisors, Hector Ceniceros and Ruimeng Hu, for their guidance and support during my time at UCSB. The process of mathematical research was especially challenging during the COVID-19 pandemic, and Hector and Ruimeng were steadfast in their support during the hardest of times. I consider myself extremely fortunate to have worked with the two of them. I am thankful to my committee, including Carlos Garcia-Cervera, along with my advisors Hector and Ruimeng. Carlos was instrumental in offering feedback for the dissertation. I wish to extend gratitude towards fellow co-authors and collaborators in my research papers. Yao Xuan, Jiequn Han as well as my aforementioned advisors all played a massive role in the research for stochastic differential games applied to COVID-19 . I am also grateful for my friends in graduate school who helped me throughout this experience. I am thankful to friends both in and outside of graduate school who have made these past years special.  \nI am filled with gratitude for my family who supported me throughout my life and education. Mom and dad, you have believed in me throughout everything and given me the opportunities to succeed. I cannot possibly express my gratitude to you in words. Matt and Lauren, you have shaped me immensely to become the person I am today, and I am extremely fortunate and beyond grateful to have you as my brother and sister. Taylor, I am incredibly lucky to know you, and you have shown unwavering support tome throughout my time in graduate school. I could not have done it without you.  \nRobert Andrew Balkin  \nEducation  \nUniversity of California, Santa Barbara  \nPh.D. in Mathematics Sep. 2017-Sep. 2023  \nMaster’s in Mathematics GPA: 4.00 Sep. 2017-Jun. 2019  \nColorado School of Mines  \n[B.S. in](B.S. in) Computational and Applied Mathematics Aug. 2013-Dec. 2016  \nPublications  \nR. Balkin, H.D. Ceniceros, and R. Hu, “Stochastic Delay Differential Games: Financial Modeling and Machine Learning Algorithms”. 2023. (Under review). [https:](https:)//[arxiv. org/pdf/2307.06450. pdf](arxiv. org/pdf/2307.06450. pdf).  \nY. Xuan, R. Balkin, J. Han, R. Hu, H.D. Ceniceros, “Optimal policies for a pandemic: a stochastic game approach and a deep learning algorithm. ” Mathematical and Scientific Machine Learning, pages 987-1012. PMLR, 2022 . [https://msml21. github. io/](https://msml21. github. io/)[ ](https://msml21. github. io/)[papers/id42. pdf](papers/id42. pdf.)[.](papers/id42. pdf.)  \nY. Xuan, R. Balkin, J. Han, R. Hu and H.D. Ceniceros,“Pandemic Control, Game Theory and Machine Learning”, Noti","cbCaic95Fl25twtB","https://ap.wps.com/l/cbCaic95Fl25twtB","pdf",6100902,1,112,"English","en",105,"# Acknowledgements\n# Education and Publications\n# Research Experience\n# Abstract","[{\"question\":\"What is the main focus of the dissertation?\",\"answer\":\"The dissertation develops machine learning methods for stochastic differential games with delay, emphasizing the computation of Nash equilibria and their predictive value.\"},{\"question\":\"Which application areas are covered?\",\"answer\":\"The work applies the framework to epidemiology (including COVID-19 dynamics and policies) and to finance (such as competitive portfolio allocation modeling).\"},{\"question\":\"How does delay affect the models considered?\",\"answer\":\"Delay is incorporated into the stochastic differential games, requiring specialized solution and machine learning approaches to handle delayed dynamics.\"}]","Machine Learning Methods for Stochastic Differential Games and those with Delay: Applications and Modeling in Epidemiology and Finance - 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