6 papers · 1 filter
Trojan horse hunt in deep forecasting models: Insights from the European Space Agency competition
Krzysztof Kotowski, Ramez Shendy, Jakub Nalepa +10
Forecasting plays a crucial role in modern safety-critical applications, such as space operations. However, the increasing use of deep forecasting models introduces a new security…
Fake or Real: The Impostor Hunt in Texts for Space Operations
Agata Kaczmarek, Dawid PÅudowski, Piotr WilczyÅski +6
The "Fake or Real" competition hosted on Kaggle (https://www.kaggle.com/competitions/fake-or-real-the-impostor-hunt ) is the second part of a series of follow-up competitions and h…
Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning
Jakub Piwko, JÄdrzej RuciÅski, Dawid PÅudowski +5
Ensemble learning has proven effective in boosting predictive performance, but traditional methods such as bagging, boosting, and dynamic ensemble selection (DES) suffer from high…
Trojan Horse Hunt in Time Series Forecasting for Space Operations
Krzysztof Kotowski, Ramez Shendy, Jakub Nalepa +6
This competition hosted on Kaggle (https://www.kaggle.com/competitions/trojan-horse-hunt-in-space) is the first part of a series of follow-up competitions and hackathons related to…
MASCOTS: Model-Agnostic Symbolic COunterfactual explanations for Time Series
Dawid PÅudowski, Francesco Spinnato, Piotr WilczyÅski +4
Counterfactual explanations provide an intuitive way to understand model decisions by identifying minimal changes required to alter an outcome. However, applying counterfactual met…
Rethinking of Encoder-based Warm-start Methods in Hyperparameter Optimization
Dawid PÅudowski, Antoni Zajko, Anna Kozak +1
Effectively representing heterogeneous tabular datasets for meta-learning purposes remains an open problem. Previous approaches rely on predefined meta-features, for example, stati…