Computational learning and model optimization - Part II of II
For Part I, see MS-Mo-D-48

Date: August 10
Time: 16:00--18:00
Room: 212B

(Note: Click title to show the abstract.)

Schönlieb, Carola-Bibiane (Univ. of Cambridge)
Chung, Matthias (Virginia Tech)
De Los Reyes, Juan Carlos (ModeMat)

Abstract: Many scientific fields such as engineering, life sciences, and geophysics encounter large scale problems where observations are contaminated with noise. To infer reliable information from experiments novel modeling techniques and inversion methods are needed. Computational learning and optimized modeling approaches are essential. To target challenges in these fields we will discuss statistical learning methods, optimization and design techniques under uncertainty, and inverse problems of big data.

Model reduction in optical imaging using a statistical approach
Tarvainen, Tanja (Univ. of Eastern Finland)

Learning in variational image regularisation
Schönlieb, Carola-Bibiane (Univ. of Cambridge)


Code: Type-Date-Time-Room No.
Type : IL=Invited Lecture, SL=Special Lectures, MS=Minisymposia, IM=Industrial Minisymposia, CP=Contributed Papers, PP=Posters
Date: Mo=Monday, Tu=Tuesday, We=Wednesday, Th=Thursday, Fr=Friday
Time : A=8:30-9:30, B=10:00-11:00, C=11:10-12:10, BC=10:00-12:10, D=13:30-15:30, E=16:00-18:00, F=19:00-20:00, G=12:10-13:30, H=15:30-16:00
Room No.: TBA