The field of interpretability investigates what machine learning (ML) models are learning from training datasets, the causes and effects of changes within a model, and the justifications behind its ...
MIT Press recently published Fundamental Proof Methods in Computer Science, a book by Konstantine Arkoudas and David Musser, a professor emeritus of computer science at the Rensselaer Polytechnic ...
The intersection of machine learning and mathematical logic — spanning computer science, pure mathematics, and statistics — has catalyzed recent advances in artificial intelligence and deep learning ...
Today the Association for Computing Machinery’s Special Interest Group on Algorithms and Computation Theory (SIGACT) and the European Association for Theoretical Computer Science (EATCS) announced ...
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