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WMLI 2016 : ICANN 2016 Workshop on Machine Learning and Interpretability | |||||||||||||
| Link: http://www.interpretable-ml.org/icann2016workshop/ | |||||||||||||
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Call For Papers | |||||||||||||
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ICANN 2016 Workshop on Machine Learning and Interpretability
Workshop at 25th International Conference on Artificial Neural Networks (ICANN) BarcelonaTech (UPC), Barcelona, Spain 6 September 2016 ============================================================ Machine learning (ML) methods such as deep neural networks have demonstrated high predictive performance on a number of tasks in the sciences and industry. However, these predictive models often behave as black-boxes, and model interpretability must be built expressly into the system. The Workshop on Machine Learning and Interpretability (WMLI2016) aims to review recent techniques for enabling the interpretability of machine learning models and to identify new fields of applications for such techniques. Furthermore, it would provide an opportunity for participants to initiate new interdisciplinary projects. For more information see http://interpretable-ml.org/icann2016workshop CALL FOR EXTENDED ABSTRACTS We welcome submission of extended abstracts related to the topic of machine learning and interpretability. There are no formatting constraints except that the abstract should be limited to 1 or 2 pages. Submission website: https://cmt3.research.microsoft.com/WMLI2016 |
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