{
	"event_id": "1021440",
	"eventinstance_id": "3928194",
	"calendar": {
		"id": 1684,
		"title": "Mathematics Department Calendar",
		"slug": "mathematics-department-calendar",
		"url": "https://events.ucf.edu/calendar/1684/mathematics-department-calendar/"
	},
	"id": "3928194",
	"title": "Colloquium by Professor Xin Li",
	"subtitle": null,
	"description": "\u003Cp\u003EOur \u003Ca href\u003D\u0022https://sciences.ucf.edu/math/colloquium/\u0022 target\u003D\u0022_blank\u0022\u003EColloquium series\u003C/a\u003E offers a vibrant platform for faculty, students, research scholars, and industry experts to share and exchange ideas, fostering discussion and networking across mathematics, statistics, and data science.\u003C/p\u003E\u000A\u003Cp\u003EThis week, our own Professor \u003Ca href\u003D\u0022https://sciences.ucf.edu/math/person/xin\u002Dli/\u0022 target\u003D\u0022_blank\u0022\u003EXin Li\u003C/a\u003E will present a talk on \u0022\u003Cem\u003EDynamic Inertial Newton Inspired Algorithms And Their Applications to Non\u002DSmooth and Non\u002DConvex Optimizations\u003C/em\u003E.\u0022\u003C/p\u003E\u000A\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C/strong\u003E \u0026nbsp\u003BDynamic Inertial Newton (DIN) systems have been used to motivate or explain several accelerated algorithms to solve a wide range of optimization problems. In this presentation, we propose new algorithms inspired by DIN and establish their convergence analysis. Furthermore, we discuss how to apply these algorithms to the applications in deep learning via a smoothing approximation approach. The motivation for our study is two\u002Dfolds: we give a direct approach to find a critical point of the objective functions, and we want to cover most problems in machine learning whose objective functions are known to be non\u002Dsmooth and non\u002Dconvex.\u0026nbsp\u003B\u003C/p\u003E\u000A\u003Cp\u003E\u003Cstrong\u003ESpeaker Bio:\u003C/strong\u003E Dr. Xin Li is a Professor of Mathematics at the University of Central Florida, where he has served since 1990, including a decade as Department Chair. He earned his Ph.D. from the University of South Florida in 1989 under Professor E.B. Saff. His research spans approximation theory, orthogonal polynomials, stochastic processes, computer vision, and machine learning, with numerous publications and international presentations. He has led or co\u002Dled major research and education projects funded by the NSF, industry, and government agencies, and is affiliated with UCF\u0026rsquo\u003Bs Center for Research in Computer Vision. An award\u002Dwinning educator, Dr. Li has guided Ph.D. and master\u0026rsquo\u003Bs students and received multiple teaching honors, reflecting his commitment to advancing mathematics and STEM education.\u003C/p\u003E",
	"location": "MSB 318: Mathematical Sciences Building, Room 318",
	"location_url": "https://www.ucf.edu/location/mathematical\u002Dsciences\u002Dbuilding/",
	"virtual_url": null,
	"registration_link": null,
	"registration_info": null,
	"starts": "Mon, 25 Aug 2025 11:00:00 -0400",
	"ends": "Mon, 25 Aug 2025 12:00:00 -0400",
	"ongoing": "False",
	"category": "Speaker/Lecture/Seminar",
	"tags": ["UCF College of Sciences","UCF Statistics","UCF Mathematics"],
	"contact_name": "Zhisheng Shuai",
	"contact_phone": null,
	"contact_email": "Zhisheng.Shuai@ucf.edu",
	"url": "https://events.ucf.edu/event/3928194/colloquium-by-professor-xin-li/"
}