Date : March 2nd 2025
Time : 10.00 am – 1.00 Pm (IST)
Venue : Via Zoom
Mode : Online
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This mini-symposium, spanning three focused sessions, provides an introduction to key concepts in nonlinear optimization and optimal control theory. It aims to equip participants with fundamental techniques and their applications in modern computational and control frameworks.
This session lays the groundwork for nonlinear optimization by covering essential topics such as convex optimization, gradient descent methods, and general nonlinear optimization frameworks. The discussion will emphasize theoretical foundations and practical implementations in various problem settings.
Building upon the first session, this segment delves into stochastic gradient descent (SGD) and its numerous variants, highlighting their significance in large-scale and nonconvex optimization. The session will explore theoretical aspects, practical considerations, and the role of SGD in machine learning applications
The final session introduces the fundamentals of optimal control, beginning with control problems for ordinary differential equations (ODEs) and the principles of feedback control. Topics will include the Riccati equation and its role in feedback synthesis, as well as constrained and unconstrained optimal control formulations. This session provides a comprehensive perspective on theoretical methods and their applications in control systems.
Saint Mary’s College
USA
University of Konstanz
Germany
This mini-symposium is designed for researchers and practitioners interested in optimization, machine learning, and control theory, offering both theoretical insights and practical motivation for further exploration.
Research and Development Centre for Mathematical Modeling
Department of Mathematics
University of Colombo
