16 citations · 17 across the 3 of their papers we have counts for
3 papers
cs.CR2024★ 1 cited
Counteracting Concept Drift by Learning with Future Malware Predictions
Branislav Bosansky, Lada Hospodkova, Michal Najman +3
The accuracy of deployed malware-detection classifiers degrades over time due to changes in data distributions and increasing discrepancies between training and testing data. This…
stat.ML2022
Explaining Classifiers Trained on Raw Hierarchical Multiple-Instance Data
Tomáš Pevný, Viliam Lisý, Branislav Bošanský +2
Learning from raw data input, thus limiting the need for feature engineering, is a component of many successful applications of machine learning methods in various domains. While m…
cs.GT2017★ 16 cited
Equilibrium Approximation Quality of Current No-Limit Poker Bots
Viliam Lisy, Michael Bowling
Approximating a Nash equilibrium is currently the best performing approach for creating poker-playing programs. While for the simplest variants of the game, it is possible to evalu…