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Found 5 papers, 3 papers with code
On Inductive Abilities of Latent Factor Models for Relational Learning
Latent factor models are increasingly popular for modeling multi-relational knowledge graphs.
Knowledge Graph Completion via Complex Tensor Factorization
In statistical relational learning, knowledge graph completion deals with automatically understanding the structure of large knowledge graphs---labeled directed graphs---and predicting missing relationships---labeled edges.
Ranked #2 on
Knowledge Graphs
on FB15k
Similarity Learning for Time Series Classification
In this paper, we propose a novel method for learning similarities based on DTW, in order to improve time series classification.
Complex Embeddings for Simple Link Prediction
In statistical relational learning, the link prediction problem is key to automatically understand the structure of large knowledge bases.
Ranked #4 on
Link Prediction
on FB122
Algorithmic Robustness for Learning via $(ε, γ, τ)$-Good Similarity Functions
The notion of metric plays a key role in machine learning problems such as classification, clustering or ranking.
