1 citations · 1 across the 5 of their papers we have counts for
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Integrating Meta-Features with Knowledge Graph Embeddings for Meta-Learning
Antonis Klironomos, Ioannis Dasoulas, Francesco Periti +4
The vast collection of machine learning records available on the web presents a significant opportunity for meta-learning, where past experiments are leveraged to improve performan…
ExeKGLib: A Platform for Machine Learning Analytics based on Knowledge Graphs
Antonis Klironomos, Baifan Zhou, Zhipeng Tan +4
Nowadays machine learning (ML) practitioners have access to numerous ML libraries available online. Such libraries can be used to create ML pipelines that consist of a series of st…
ReaLitE: Enrichment of Relation Embeddings in Knowledge Graphs using Numeric Literals
Antonis Klironomos, Baifan Zhou, Zhuoxun Zheng +3
Most knowledge graph embedding (KGE) methods tailored for link prediction focus on the entities and relations in the graph, giving little attention to other literal values, which m…
ExeKGLib: Knowledge Graphs-Empowered Machine Learning Analytics
Antonis Klironomos, Baifan Zhou, Zhipeng Tan +4
Many machine learning (ML) libraries are accessible online for ML practitioners. Typical ML pipelines are complex and consist of a series of steps, each of them invoking several ML…