IST - Real Analysis and its Applications to Approximation and Learning Theory (2026)
Venue: Sri Sivasubramaniya Nadar College of Engineering, kalavakkam
Dates: 1 Jun 2026 to 13 Jun 2026
|
Convener(s) |
||||
| Name: | Prof. A. Swaminathan | Prof. B. Praba | Dr. A. Sathish Kumar | Dr. S. Yugesh |
| Mailing Address: | Professor Deparment of Mathematics IIT Roorkee, Roorkee 247667 |
Professor & Head Department of Mathematics SSN College of Engineering, Kalavakkam , Tamil Nadu. 603 110 |
Assistant Professor Deparment of Mathematics IIT Madras, Chennai 600 036 |
Assistant Professor Department of Mathematics SSN College of Engineering, Kalavakkam ,Tamil Nadu, 603 110 |
| Email: | a.swaminathan at ma.iitr.ac.in | prabab at ssn.edu.in | sathishkumar at iitm.ac.in | yugeshs at ssn.edu.in |
Real Analysis forms the foundation of modern mathematics and plays a central role in various branches of analysis, with significant applications in approximation theory and learning theory. A solid understanding of real analysis is essential not only for exploring the structure and properties of functions and spaces, but also for developing rigorous methods in approximation and data-driven learning.
The instructional school aims to provide participants with a guided tour of the core concepts in Real Analysis and their connections to Approximation Theory and Learning Theory. It will also introduce advanced tools and applications such as best approximation, Padé approximation and real analytic functions, Shannon’s sampling theorem, convergence of sampling operators, the universal approximation theorem, reproducing kernel Hilbert spaces, and convergence analysis of regularized learning algorithms.
The topics are chosen to give participants exposure to both classical and modern perspectives in analysis and its applications, thereby strengthening their background for further research in mathematics, applied analysis, and data science.