94 citations · 169 across the 10 of their papers we have counts for
12 papers
Small molecule retrieval from tandem mass spectrometry: what are we optimizing for?
Gaetan De Waele, Marek Wydmuch, Krzysztof Dembczyński +2
One of the central challenges in the computational analysis of liquid chromatography-tandem mass spectrometry (LC-MS/MS) data is to identify the compounds underlying the output spe…
A General Online Algorithm for Optimizing Complex Performance Metrics
Wojciech Kotłowski, Marek Wydmuch, Erik Schultheis +2
We consider sequential maximization of performance metrics that are general functions of a confusion matrix of a classifier (such as precision, F-measure, or G-mean). Such metrics…
Consistent algorithms for multi-label classification with macro-at- metrics
Erik Schultheis, Wojciech Kotłowski, Marek Wydmuch +3
We consider the optimization of complex performance metrics in multi-label classification under the population utility framework. We mainly focus on metrics linearly decomposable i…
Generalized test utilities for long-tail performance in extreme multi-label classification
Erik Schultheis, Marek Wydmuch, Wojciech Kotłowski +2
Extreme multi-label classification (XMLC) is the task of selecting a small subset of relevant labels from a very large set of possible labels. As such, it is characterized by long-…
On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification
Erik Schultheis, Marek Wydmuch, Rohit Babbar +1
The propensity model introduced by Jain et al. 2016 has become a standard approach for dealing with missing and long-tail labels in extreme multi-label classification (XMLC). In th…
Propensity-scored Probabilistic Label Trees
Marek Wydmuch, Kalina Jasinska-Kobus, Rohit Babbar +1
Extreme multi-label classification (XMLC) refers to the task of tagging instances with small subsets of relevant labels coming from an extremely large set of all possible labels. R…
Probabilistic Label Trees for Extreme Multi-label Classification
Kalina Jasinska-Kobus, Marek Wydmuch, Krzysztof Dembczynski +2
Extreme multi-label classification (XMLC) is a learning task of tagging instances with a small subset of relevant labels chosen from an extremely large pool of possible labels. Pro…
Online probabilistic label trees
Kalina Jasinska-Kobus, Marek Wydmuch, Devanathan Thiruvenkatachari +1
We introduce online probabilistic label trees (OPLTs), an algorithm that trains a label tree classifier in a fully online manner without any prior knowledge about the number of tra…
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…
A no-regret generalization of hierarchical softmax to extreme multi-label classification
Marek Wydmuch, Kalina Jasinska, Mikhail Kuznetsov +2
Extreme multi-label classification (XMLC) is a problem of tagging an instance with a small subset of relevant labels chosen from an extremely large pool of possible labels. Large l…
ViZDoom Competitions: Playing Doom from Pixels
Marek Wydmuch, Michał Kempka, Wojciech Jaśkowski
This paper presents the first two editions of Visual Doom AI Competition, held in 2016 and 2017. The challenge was to create bots that compete in a multi-player deathmatch in a fir…
ViZDoom: A Doom-based AI Research Platform for Visual Reinforcement Learning
Michał Kempka, Marek Wydmuch, Grzegorz Runc +2
The recent advances in deep neural networks have led to effective vision-based reinforcement learning methods that have been employed to obtain human-level controllers in Atari 260…