1 citations · 4 across the 17 of their papers we have counts for
3 papers · 2 filters
Understanding Aggregations of Proper Learners in Multiclass Classification
Julian Asilis, Mikael Møller Høgsgaard, Grigoris Velegkas
Multiclass learnability is known to exhibit a properness barrier: there are learnable classes which cannot be learned by any proper learner. Binary classification faces no such bar…
The Many Faces of Optimal Weak-to-Strong Learning
Mikael Møller Høgsgaard, Kasper Green Larsen, Markus Engelund Mathiasen
Boosting is an extremely successful idea, allowing one to combine multiple low accuracy classifiers into a much more accurate voting classifier. In this work, we present a new and…
Optimal Parallelization of Boosting
Arthur da Cunha, Mikael Møller Høgsgaard, Kasper Green Larsen
Recent works on the parallel complexity of Boosting have established strong lower bounds on the tradeoff between the number of training rounds and the total parallel work per r…