Welcome to my personal website, below you will find some of the things I've made and done:
Most recent news & events
- 02.2023New version of Vowpal Wabbit (9.7.0) was released with my improved implementation of PLT reduction.
- 11.2022Me and ViZDoom project joined The Farama Foundation.
- 06.2022I started an internship at Yahoo! in Paris, France.
- 05.2022Our paper titled "On missing labels, long-tails and propensities in extreme multi-label classification" was accepted at KDD'22.
- 03.2022New release of ViZDoom (1.1.12) library with new official OpenAI Gym wrapper.
- 01.2022I joined the management board of ML in PL Association.
- 11.2021New release of ViZDoom (1.1.11) library with new features, including access to the game's audio buffer.
- 08.2021Our paper "ViZDoom Competitions: Playing Doom From Pixels" received 2022 IEEE ToG Outstanding Paper Award.
- 04.2021Our short paper titled "Propensity-scored Probabilistic Label Trees" was accepted at SIGIR'21.
- 03.2021Our paper titled "Efficient Set-Valued Prediction in Multi-Class Classification" was accepted for publication in Data Mining and Knowledge Discovery.
- 02.2021Our paper titled "Online probabilistic label trees" was accepted at AISTATS'21.
- 12.2020I gave a talk titled "Probabilistic Label Trees in Vowpal Wabbit" at Vowpal Wabbit Workshop at NeurIPS'20. [ video]
- 10.2020I gave a talk titled "Extreme classification: applications and algorithms" on GHOST Day: AMLC'20. [ video]
Publications
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On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification
Erik Schultheis, Marek Wydmuch, Rohit Babbar, Krzysztof Dembczyński
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), 2022
[ paper] [ poster] [ bibtex] -
Propensity-scored Probabilistic Label Trees
Marek Wydmuch, Kalina Jasinska-Kobus, Rohit Babbar, Krzysztof Dembczyński
Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '21), 2021
[ code (napkinXC)] [ paper] [ poster] [ bibtex] -
Online probabilistic label trees
Kalina Jasinska-Kobus, Marek Wydmuch, Devanathan Thiruvenkatachari, Krzysztof Dembczyński
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS 2021), 2021
[ code (napkinXC)] [ paper] [ poster] [ AISTATS 2021 talk] [ ICML XC 2020 talk] [ bibtex] -
Efficient set-valued prediction in multi-class classification
Thomas Mortier, Marek Wydmuch, Krzysztof Dembczyński, Eyke Hüllermeier, Willem Waegeman
Data Mining and Knowledge Discovery, 2021
[ paper] [ bibtex] -
Probabilistic Label Trees for Extreme Multi-label Classification
Kalina Jasinska-Kobus, Marek Wydmuch, Krzysztof Dembczyński
Submitted to Journal of Machine Learning Research, 2020
[ code (napkinXC)] [ bibtex] -
A no-regret generalization of hierarchical softmax to extreme multi-label classification
Marek Wydmuch, Kalina Jasinska-Kobus, Mikhail Kuznetsov, Robert Busa-Fekete, Krzysztof Dembczyński
Proceedings of the 32nd International Conference on Neural Information Processing Systems (NeurIPS 2018), 2018
[ code (extremeText)] [ paper] [ poster] [ bibtex] -
ViZDoom Competitions: Playing Doom From Pixels
Marek Wydmuch, Michał Kempka, Wojciech Jaśkowski
IEEE Transactions on Games, 2018
Note: 2022 IEEE ToG Outstanding Paper Award
[ paper] [ movies] [ bibtex] -
ViZDoom: A Doom-based AI research platform for visual reinforcement learning
Michał Kempka, Marek Wydmuch, Grzegorz Runc, Jakub Toczek, Wojciech Jaśkowski
2016 IEEE Conference on Computational Intelligence and Games (CIG 2016), 2016
Note: 2016 IEEE CIG The Best Paper Award
[ www] [ code] [ paper] [ bibtex]
Software
ViZDoom
Doom-based AI Research Platform for Reinforcement Learning from Raw Visual Information.[ www] [ code]
napkinXC
Extremely simple and fast library for extreme multi-class and multi-label classification.[ code]
extremeText
Extension of fastText library for multi-label classification including extreme cases with hundreds of thousands and millions of labels.[ code]
ML in PL
I'm proud to be a member of the awesome ML in PL Association, a non-profit organization devoted to fostering the machine learning community in Poland and around the world.
From 2021 I'm a member of the management board of ML in PL Association and try to support other members of the association in the organization of great machine learning related events.
Before I co-organized ML in PL Conference 2019, ML in PL Virtual Event 2020, and ML in PL Conference 2021 serving as Call for Contributions (Talks and Posters) coordinator.
Reviewing scientific papers
I try to review at least a dozen of papers each year. So far I have served as a reviewer for:- Conferences:
- NeurIPS 2020, 2021 (Outstanding Reviewer Award - top 8%), and 2022 (Top Reviewer Award - top 8%)
- ICML 2021, and 2022, and 2023
- ICLR 2022, and 2023
- IJCAI 2020, and 2021
- AISTATS 2021
-
Journals:
- IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)
- Machine Learning Journal
- Transactions on Machine Learning Research (TMLR)
Teaching
As part of my PhD, I teach/teached a few courses at Poznan University of Technology (PUT) related to the topics of Machine Learning, Artificial Intelligence, and Data Science and Big Data:- Advanced Methods of Computational Intelligence 2021, 2022 and 2023 (lectures + exercises)
based on Richard S. Sutton and Andrew G. Barto, Reinforcement Learning: An Introduction and selected chapters from Stuart Russell and Peter Norvig, Artificial Intelligence A Modern Approach. - Methods of Artificial and Computational Intelligence 2021 (exercises)
based on selected chapters from Stuart Russell and Peter Norvig, Artificial Intelligence A Modern Approach. - Big Data Processing 2019/2020 and Processing of Massive Datasets 2018/2019 (exercises)
based on selected chapters from Jure Leskovec, Anand Rajaraman, Jeff Ullman, Mining of Massive Datasets. - Information Theory and Lossless Compression Methods 2018 (exercises)
based on the first chapters from David J.C. MacKay, Information Theory, Inference, and Learning Algorithms.
Note: The course was awarded as the best new course in 2018 at the Institute of Computer Science.