Workshop on Machine Learning and Interpretability (WMLI 2016)

September 6, 2016

Barcelona, Spain

Call For Papers

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.

Topics of Interest

We welcome in particular contributions on:


• The analysis and visualization of machine learning predictions (e.g. deep network classifications).
• Methods for extraction of interpretable knowledge from machine learning models.
• The identification of new applications that benefit from interpretable machine learning.

IMPORTANT DATES

Submission deadline: August 16, 2016

Notification Due: August 19 , 2016

Final Version Due: August 26, 2016

                       

User Name : jerish
Posted 02-08-2016 on 09:51:30 AEDT

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