Boolean Classifier

Boolean classifiers, which assign data points to one of two categories, are a fundamental tool in machine learning, with research focusing on improving accuracy, interpretability, and robustness in various settings. Current efforts explore efficient algorithms for constructing Boolean classifiers from tabular data, analyzing the expressiveness of graph neural networks (GNNs) as Boolean classifiers, and addressing challenges posed by strategic agents who manipulate input features to influence classification outcomes. These advancements have implications for diverse applications, ranging from improving the explainability of AI systems to developing more resilient online learning algorithms.