ATPboost: learning premise selection in binary setting with ATP feedback
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Publication:1799117
DOI10.1007/978-3-319-94205-6_37OpenAlexW2963407845MaRDI QIDQ1799117
Josef Urban, Bartosz Piotrowski
Publication date: 18 October 2018
Full work available at URL: https://arxiv.org/abs/1802.03375
Learning and adaptive systems in artificial intelligence (68T05) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)
Related Items (6)
Online machine learning techniques for Coq: a comparison ⋮ Improving stateful premise selection with transformers ⋮ Alien coding ⋮ Towards the automatic mathematician ⋮ ENIGMA-NG: efficient neural and gradient-boosted inference guidance for \(\mathrm{E}\) ⋮ ATPboost
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