19 citations · 52 across the 21 of their papers we have counts for
6 papers · 1 filter
Learning Horn Envelopes via Queries from Large Language Models
Sophie Blum, Raoul Koudijs, Ana Ozaki +1
We investigate an approach for extracting knowledge from trained neural networks based on Angluin's exact learning model with membership and equivalence queries to an oracle. In th…
Verifying Properties of Tsetlin Machines
Emilia Przybysz, Bimal Bhattarai, Cosimo Persia +3
Tsetlin Machines (TsMs) are a promising and interpretable machine learning method which can be applied for various classification tasks. We present an exact encoding of TsMs into p…
On the Effectiveness of Knowledge Graph Embeddings: a Rule Mining Approach
Johanna Jøsang, Ricardo Guimarães, Ana Ozaki
We study the effectiveness of Knowledge Graph Embeddings (KGE) for knowledge graph (KG) completion with rule mining. More specifically, we mine rules from KGs before and after they…
Extracting Rules from Neural Networks with Partial Interpretations
Cosimo Persia, Ana Ozaki
We investigate the problem of extracting rules, expressed in Horn logic, from neural network models. Our work is based on the exact learning model, in which a learner interacts wit…
Exact Learning of Lightweight Description Logic Ontologies
Boris Konev, Carsten Lutz, Ana Ozaki +1
We study the problem of learning description logic (DL) ontologies in Angluin et al.'s framework of exact learning via queries. We admit membership queries ("is a given subsumption…
New Steps on the Exact Learning of CNF
Montserrat Hermo, Ana Ozaki
A major problem in computational learning theory is whether the class of formulas in conjunctive normal form (CNF) is efficiently learnable. Although it is known that this class ca…