4 citations · 6 across the 6 of their papers we have counts for
8 papers
Supervised Classification: Quite a Brief Overview
Marco Loog
The original problem of supervised classification considers the task of automatically assigning objects to their respective classes on the basis of numerical measurements derived f…
Object-Extent Pooling for Weakly Supervised Single-Shot Localization
Amogh Gudi, Nicolai van Rosmalen, Marco Loog +1
In the face of scarcity in detailed training annotations, the ability to perform object localization tasks in real-time with weak-supervision is very valuable. However, the computa…
On Measuring and Quantifying Performance: Error Rates, Surrogate Loss, and an Example in SSL
Marco Loog, Jesse H. Krijthe, Are C. Jensen
In various approaches to learning, notably in domain adaptation, active learning, learning under covariate shift, semi-supervised learning, learning with concept drift, and the lik…
Scale-Regularized Filter Learning
Marco Loog, François Lauze
We start out by demonstrating that an elementary learning task, corresponding to the training of a single linear neuron in a convolutional neural network, can be solved for feature…
Nuclear Discrepancy for Active Learning
Tom J. Viering, Jesse H. Krijthe, Marco Loog
Active learning algorithms propose which unlabeled objects should be queried for their labels to improve a predictive model the most. We study active learners that minimize general…
Active Learning Using Uncertainty Information
Yazhou Yang, Marco Loog
Many active learning methods belong to the retraining-based approaches, which select one unlabeled instance, add it to the training set with its possible labels, retrain the classi…