Schedule

The scheduled seminars will be posted on this page; please visit the page occasionally.

Please keep in mind that upcoming talks might be postponed to some future time.

Also, all seminars will be ONLINE, unless otherwise is explicitly stated!

Scheduled Seminars

• A Learning Theory for Bilevel Optimization in Machine Learning via RKHS

  by Michael N. Arbel

  Speaker: Michael N. Arbel (THOTH Team, INRIA Grenoble - Rhône-Alpes, France)

  Date / Time: Thursday, February 13, 2025 / 15:30 (Ankara, Turkey)

  Place: Follow the Link for Online Participation (please self-register first, if necessary)

• TBA - Scheduled Date Might be Changed too!

  by Arthur Gretton

  Speaker: Arthur Gretton (Gatsby Computational Neuroscience Unit, Centre for Computational Statistics and Machine Learning, University College London (UCL), UK)

  Date / Time: Tuesday, January 14, 2025 / 15:30 (Ankara, Turkey)

  Place: Follow the Link for Online Participation (please self-register first, if necessary)

• Probability Error Bounds for Approximation of Functions in Reproducing Kernel Hilbert Spaces

  by Aurelian Gheondea

  Additional Resources:
  - Presentation Slides - Recorded Video (Raw)
• Bridging Machine Learning, Dynamical Systems, and Algorithmic Information Theory: Insights from Sparse Kernel Flows, Poincaré Normal Forms and PDE Simplification

  by Boumediene Hamzi

  Additional Resources:
  - Recorded Video (Raw)
• Machine Learning and Dynamical Systems meet in Reproducing Kernel Hilbert Spaces: Part I

  by Boumediene Hamzi

  Additional Resources:
  - Presentation Slides - Recorded Video (Raw)
• Kernel Methods: applications, promises and open issues

  by Jean-Marc Mercier

  Additional Resources:
  - Presentation Slides - Recorded Video (Raw) - CodPy: a Python library for numerics, machine learning, and statistics
• Stochastic Processes and the RKHS

  by Azize Hayfavi

  Additional Resources:
  - Stochastic Processes (Notes)
• Fundamental Properties of Reproducing Kernels and RKHSs

  by Baver Okutmuştur

  Additional Resources:
  - Fundamental Properties of RKHS (Slides) - Theory of Reproducing Kernels and Applications
• Vectors, Matrices, Maps and the finite-dimensional RKHSs - Part III

  by Ömür Uğur

  Additional Resources:
  - Orthogonal Projections (Slides) - Basics of RKHS (Slides) - Finite Dimensional RKHSs (Slides)
• A Brief Introduction to Hilbert Space Theory with RKHS in Mind - Part II

  by Aydın Aytuna

  Additional Resources:
  - Lecture Notes - Presentation Slides
• A Brief Introduction to Hilbert Space Theory with RKHS in Mind

  by Aydın Aytuna

  Additional Resources:
  - Lecture Notes - Presentation Slides
• Vectors, Matrices, Maps and the finite-dimensional RKHSs - Part II

  by Ömür Uğur

  Additional Resources:
  - Orthogonal Projections (Slides) - Basics of RKHS (Slides) - Finite Dimensional RKHSs (Slides)
• Vectors, Matrices, Maps and the finite-dimensional RKHSs

  by Ömür Uğur

  Additional Resources:
  - Orthogonal Projections (Slides) - Basics of RKHS (Slides) - Finite Dimensional RKHSs (Slides)
• Kernels and RKHS

  by Bülent Karasözen

  Additional Resources:
  - Presentation Slides - Recorded Video (Raw)