3 citations · 4 across the 3 of their papers we have counts for
8 papers
Hyperparameter optimization in deep multi-target prediction
Dimitrios Iliadis, Marcel Wever, Bernard De Baets +1
As a result of the ever increasing complexity of configuring and fine-tuning machine learning models, the field of automated machine learning (AutoML) has emerged over the past dec…
Set-valued prediction in hierarchical classification with constrained representation complexity
Thomas Mortier, Eyke Hüllermeier, Krzysztof Dembczyński +1
Set-valued prediction is a well-known concept in multi-class classification. When a classifier is uncertain about the class label for a test instance, it can predict a set of class…
Multi-target prediction for dummies using two-branch neural networks
Dimitrios Iliadis, Bernard De Baets, Willem Waegeman
Multi-target prediction (MTP) serves as an umbrella term for machine learning tasks that concern the simultaneous prediction of multiple target variables. Classical instantiations…
Efficient Set-Valued Prediction in Multi-Class Classification
Thomas Mortier, Marek Wydmuch, Krzysztof Dembczyński +2
In cases of uncertainty, a multi-class classifier preferably returns a set of candidate classes instead of predicting a single class label with little guarantee. More precisely, th…
Multi-Target Prediction: A Unifying View on Problems and Methods
Willem Waegeman, Krzysztof Dembczynski, Eyke Huellermeier
Multi-target prediction (MTP) is concerned with the simultaneous prediction of multiple target variables of diverse type. Due to its enormous application potential, it has develope…
A Comparative Study of Pairwise Learning Methods based on Kernel Ridge Regression
Michiel Stock, Tapio Pahikkala, Antti Airola +2
Many machine learning problems can be formulated as predicting labels for a pair of objects. Problems of that kind are often referred to as pairwise learning, dyadic prediction or…