Publications and Preprints

The Shape of Learning Curves: a Review
Tom Viering, Marco Loog
arxiv 2021
code

A Brief Prehistory of Double Descent
Marco Loog, Tom Viering, Alexander Mey, Jesse H. Krijthe, David M.J. Tax
PNAS 2020

Making Learners (More) Monotone
Tom Viering, Alexander Mey, Marco Loog
IDA 2020
code slides video

A Brief Prehistory of Double Descent
Marco Loog, Tom Viering, Alexander Mey, Jesse H. Krijthe, David M.J. Tax
arxiv preprint 2020

A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization
Alexander Mey, Tom Julian Viering, Marco Loog
IDA 2020

Making Learners (More) Monotone
Tom Viering, Alexander Mey, Marco Loog
arxiv preprint 2019

How to Manipulate CNNs to Make Them Lie: the GradCAM Case
Tom Viering, Ziqi Wang, Marco Loog, Elmar Eisemann
arxiv preprint 2019
slides

Minimizers of the Empirical Risk and Risk Monotonicity
Marco Loog, Tom Viering, Alexander Mey
in NeurIPS 2019
code slides poster

A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization
A Mey, T Viering, M Loog
arxiv preprint 2019

Nuclear discrepancy for single-shot batch active learning
Tom J Viering, Jesse H Krijthe, Marco Loog
in Machine Learning 2019
code slides poster

Open Problem: Monotonicity of Learning
T Viering, A Mey, M Loog
in COLT 2019

Nuclear Discrepancy for Active Learning
Tom J Viering, Jesse H Krijthe, Marco Loog
arxiv preprint 2017

Generalization Bound Minimization for Active Learning
Tom J Viering, Jesse H Krijthe, Marco Loog
in Benelearn 2017

Active Learning by Discrepancy Minimization: A Comparison of Active Learning Methods Motivated by Generalization Bounds
T J Viering
masterthesis 2016

Talks

In my lab, we often give short talks about selected papers we like. You can find the papers I've given talks about below.

Work

PhD Candidate @TU Delft

OCT 2016 - NOW

Education

Master Computer Science @TU Delft

SEP 2013 - AUG 2016

During my masters in Delft I discovered my passion for Machine Learning. I spent a long time on my masters project, simply because I loved it so much. My supervisors were Marco Loog and Jesse Krijthe, and we studied the problem of Active Learning using generalization bounds, in particular using the Discrepancy measure. View the abstract of my master thesis.

Bachelor Physics @Leiden University

SEP 2009 - AUG 2013

While I really enjoyed physics in my bachelor, in the end of my bachelor I fell in love with computer science (CS). During my bachelor project I built an application to control an electron microscope (EM) to record a giant mosaic of images as fast and accurate as possible. I also worked together with Frank Faas to develop a basic application to annotate and view gigabyte-size EM images. You can view the zebrafish dataset of the KosterLab research group here, which was in part annotated with help of software that Frank and I wrote. I spent the fourth year of my (physics) bachelor studying Computer Science in order to switch to my CS master at TU Delft.

Interests

Social Media