{"675587":{"#nid":"675587","#data":{"type":"event","title":"Ph.D. Dissertation Defense - Tianrong Chen","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E\u003Cem\u003E:\u0026nbsp; Bridging the Connection between Deep Learning and Stochastic Optimal Control\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EDr.\u0026nbsp;Evangelos Theodorou, AE, Chair, Advisor\u003C\/p\u003E\u003Cp\u003EDr.\u0026nbsp;Matthieu Bloch, ECE, Chair, Co-Advisor\u003C\/p\u003E\u003Cp\u003EDr.\u0026nbsp;Justin Romberg, ECE\u003C\/p\u003E\u003Cp\u003EDr.\u0026nbsp;Molei Tao, Math\u003C\/p\u003E\u003Cp\u003EDr.\u0026nbsp;Shuangfei Zhai, Apple\u003C\/p\u003E\u003Cp\u003EDr.\u0026nbsp;Yao Xie, ISyE\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGenerative models have gained significant popularity in recent years, and Stochastic Optimal Control soc has also advanced rapidly in parallel. This thesis addresses the prob- lem of understanding dynamical generative models from the perspective of Stochastic Opti- mal Control, thereby providing insights from the well-established Stochastic Optimal Con- trol theory. Additionally, it explores the challenges of high-dimensional Stochastic Optimal Control by leveraging deep learning techniques. Through this dual approach, the research aims to enhance the theoretical understanding and practical application of generative mod- els and Stochastic Optimal Control in complex, high-dimensional environments.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Bridging the Connection between Deep Learning and Stochastic Optimal Control "}],"uid":"28475","created_gmt":"2024-07-24 22:17:05","changed_gmt":"2024-07-24 22:19:16","author":"Daniela Staiculescu","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-07-29T15:00:00-04:00","event_time_end":"2024-07-29T17:00:00-04:00","event_time_end_last":"2024-07-29T17:00:00-04:00","gmt_time_start":"2024-07-29 19:00:00","gmt_time_end":"2024-07-29 21:00:00","gmt_time_end_last":"2024-07-29 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"CODA Atlantic","extras":[],"related_links":[{"url":"https:\/\/gatech.zoom.us\/j\/6943444592?pwd=b7kidU38Qn66epIlqa805MGu6QZyyU.1","title":"Zoom link"}],"groups":[{"id":"434381","name":"ECE Ph.D. Dissertation Defenses"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"},{"id":"1808","name":"graduate students"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}