• Graduate Program
  • Research
  • Browse our Courses
  • Events
    • Events Calendar
    • Events Archive
    • Tinbergen Institute Lectures
    • Summer School
      • Deep Learning
      • Economics of Blockchain and Digital Currencies
      • Foundations of Machine Learning with Applications in Python
      • Marketing Research with Purpose
      • Modern Toolbox for Spatial and Functional Data
      • Sustainable Finance
      • Tuition Fees and Payment
      • Tinbergen Institute Summer School Program
    • Annual Tinbergen Institute Conference archive
  • News
  • Summer School
    • Deep Learning
    • Economics of Blockchain and Digital Currencies
    • Foundations of Machine Learning with Applications in Python
    • Marketing Research with Purpose
    • Modern Toolbox for Spatial and Functional Data
    • Sustainable Finance
  • Alumni
Home | Events Archive | Online Change Point Detection for Regression Coefficients via weighted Empirical Risk Minimization
Research Master Pre-Defense

Online Change Point Detection for Regression Coefficients via weighted Empirical Risk Minimization


  • Location
    Vrije Universiteit Amsterdam, room HG-01A43
    Amsterdam
  • Date and time

    July 07, 2026
    15:00 - 17:00

This thesis studies online change-point detection for changes in linear regression coefficients. The goal is to detect, as new data arrive, whether the relationship between covariates and the response variable has changed. The proposed method is based on weighted empirical risk minimisation. At each step, the procedure looks at a recent window of observations and compares a one-regime regression model with a two-regime model that allows for a possible change point. If the two-regime model improves the fit sufficiently, the procedure raises an alarm.