Dear researchers,

Centrum Wiskunde & Informatica (CWI) kindly invites you sixth Seminar++ meeting on Machine Learning Theory, taking place on Wednesday May 24 from 15:00 - 17:00. These Seminar++ meetings consist of a one-hour lecture building up to an open problem, followed by an hour of brainstorming time. The meeting is intended for interested researchers including PhD students. These meetings are freely accessible without registration. Cookies, coffee and tea will be provided in the half-time break.

The meeting of 24 May will be hosted by:

Sophie Langer Assistant Professsor at the University of Twente

Image classification: A (new) statistical viewpoint

Abstract: In this talk we consider a simple supervised classification problem for object recognition on grayscale images. There are two possible perspectives to solve this problem. Firstly, one can interpret object recognition as a high-dimensional classification problem, where every pixel is a variable. The task is then to map these pixel values to the conditional class probabilities or the labels. Increasing the dimension makes the problem considerably harder, leading to slow convergence rates due to the curse of dimensionality. Another perspective is to view images as two-dimensional objects. Increasing the number of pixels leads to higher resolution and therefore better performance is expected for large images. Following the second route, we present a new image deformation model, for which we propose and analyze two different classifiers. The first method estimates the image deformation by support alignment. Under a minimal separation condition, it is shown that perfect classification is possible. The second method fits a CNN to the data. We derive a rate for the misclassification error depending on the sample size and the number of pixels d². Both classifiers are empirically compared on images generated from the MNIST handwritten digit database.

The event takes place in room L016 in the CWI building, Science Park 123, Amsterdam.

The Seminar++ Meetings are part of the Machine Learning Theory Semester Programme, which runs in Spring 2023.

Best regards on behalf of CWI from the program committee,

Wouter Koolen