Aggregating Predictors: A Theoretical Perspective
Navn på bevillingshaver
Mikael Møller Høgsgaard
Titel
Soon to graduate PhD-student
Institution
University of Oxford
Beløb
DKK 2,713,000
År
2025
Bevillingstype
Internationalisation Fellowships
Hvad?
In learning theory, the aim is to define a mathematical link between the amount of training data and the accuracy of a given prediction model. This relationship enables either ensuring a specific prediction accuracy with a given amount of training data or calculating the amount of data needed for a target accuracy. This project seeks to explore these relationships for aggregation of predictors.
Hvorfor?
The hope of establishing such relationships between the amount of training data provided to a prediction model and its accuracy is to gain insights into when and how learning occurs and what can be inferred from data.
Hvordan?
To establish such relationships, one assumes an underlying learning model or task and then, based on this model, derives mathematical guarantees on the relationship between the amount of training data provided to a prediction model and its achieved accuracy.