Feb 24, 2022 · We propose the first method for learning these relational features using a Gaifman graph by using relational tree distances.

Non-Parametric Learning of Embeddings for. Relational Data using Gaifman Locality Theorem ... Comparison with Statistical Relational Learning Methods.

Oct 25, 2021 · We propose the first method for learning these relational features using a Gaifman graph by using relational tree distances.

Non-parametric Learning of Embeddings for Relational Data Using Gaifman Locality Theorem. / Dhami, Devendra Singh; Yan, Siwen; Kunapuli, Gautam et al. 2021. 95- ...

To this effect, we construct embeddings using symbolic trees learned in a non-parametric manner. The trees are treated as a decision-list of first order rules ...

To this effect, we construct embeddings using symbolic trees learned in a non-parametric manner. The trees are treated as a decision-list of first order rules ...

Non-parametric Learning of Embeddings for Relational Data Using Gaifman Locality Theorem. https://doi.org/10.1007/978-3-030-97454-1_7 ·.

Duration: 8:35
Posted: Nov 5, 2021

Missing: Embeddings Theorem.

Non-parametric Learning of Embeddings for Relational Data Using Gaifman Locality Theorem. DS Dhami, S Yan, G Kunapuli, S Natarajan. International Conference ...