136 citations · 136 across the 1 of their papers we have counts for
3 papers
On Inductive Abilities of Latent Factor Models for Relational Learning
Théo Trouillon, Éric Gaussier, Christopher R. Dance +1
Latent factor models are increasingly popular for modeling multi-relational knowledge graphs. By their vectorial nature, it is not only hard to interpret why this class of models w…
Complex Embeddings for Simple Link Prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel +2
In statistical relational learning, the link prediction problem is key to automatically understand the structure of large knowledge bases. As in previous studies, we propose to sol…
LSHTC: A Benchmark for Large-Scale Text Classification
Ioannis Partalas, Aris Kosmopoulos, Nicolas Baskiotis +6
LSHTC is a series of challenges which aims to assess the performance of classification systems in large-scale classification in a a large number of classes (up to hundreds of thous…