MLNov 27, 2017

Proceedings of NIPS 2017 Symposium on Interpretable Machine Learning

arXiv:1711.09889v37 citations
Originality Synthesis-oriented
AI Analysis

It compiles discussions on interpretability, but is not a research paper with incremental or novel findings.

This is a proceedings document for a symposium on interpretable machine learning, presenting no specific research problem or results.

This is the Proceedings of NIPS 2017 Symposium on Interpretable Machine Learning, held in Long Beach, California, USA on December 7, 2017

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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