2 code implementations • 23 Sep 2020 • Kalina Jasinska-Kobus, Marek Wydmuch, Krzysztof Dembczynski, Mikhail Kuznetsov, Robert Busa-Fekete
We first introduce the PLT model and discuss training and inference procedures and their computational costs.
no code implementations • 1 Jun 2019 • Robert Busa-Fekete, Krzysztof Dembczynski, Alexander Golovnev, Kalina Jasinska, Mikhail Kuznetsov, Maxim Sviridenko, Chao Xu
First, we show that finding a tree with optimal training cost is NP-complete, nevertheless there are some tractable special cases with either perfect approximation or exact solution that can be obtained in linear time in terms of the number of labels $m$.
no code implementations • 7 Sep 2018 • Willem Waegeman, Krzysztof Dembczynski, Eyke Huellermeier
Multi-target prediction (MTP) is concerned with the simultaneous prediction of multiple target variables of diverse type.
no code implementations • 14 Jun 2016 • Michiel Stock, Krzysztof Dembczynski, Bernard De Baets, Willem Waegeman
Many complex multi-target prediction problems that concern large target spaces are characterised by a need for efficient prediction strategies that avoid the computation of predictions for all targets explicitly.
no code implementations • NeurIPS 2015 • Róbert Busa-Fekete, Balázs Szörényi, Krzysztof Dembczynski, Eyke Hüllermeier
In this paper, we study the problem of F-measure maximization in the setting of online learning.
no code implementations • 17 Oct 2013 • Willem Waegeman, Krzysztof Dembczynski, Arkadiusz Jachnik, Weiwei Cheng, Eyke Hullermeier
The F-measure, which has originally been introduced in information retrieval, is nowadays routinely used as a performance metric for problems such as binary classification, multi-label classification, and structured output prediction.