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Human-centric Transfer Learning Explanation via Knowledge Graph [Extended Abstract]
[article]
2019
arXiv
pre-print
Transfer learning which aims at utilizing knowledge learned from one problem (source domain) to solve another different but related problem (target domain) has attracted wide research attentions. However, the current transfer learning methods are mostly uninterpretable, especially to people without ML expertise. In this extended abstract, we brief introduce two knowledge graph (KG) based frameworks towards human understandable transfer learning explanation. The first one explains the
arXiv:1901.08547v1
fatcat:52bqpgmp5vemtcker4psazfcwy