posted by organizer: Aholzinger || 3116 views || tracked by 11 users: [display]

PAML 2016 : Privacy Aware Machine Learning for Health Data Science

FacebookTwitterLinkedInGoogle

Link: http://hci-kdd.org/privacy-aware-machine-learning-for-data-science/
 
When Aug 29, 2016 - Sep 2, 2016
Where Salzburg
Submission Deadline Apr 1, 2016
Final Version Due Jun 8, 2016
Categories    machine learning   privacy   open data   anonymization
 

Call For Papers

Machine learning is the fastest growing field in computer science, and health informatics is amongst the greatest challenges, e.g. large-scale aggregate analyses of anonymized data can yield valuable insights addressing public health challenges and provide new starting points for scientific discovery. Privacy issues are becoming a major concern for machine learning tasks, which often operate on personal and sensitive data. Consequently, privacy, data protection, safety, information security and fair use of data is of utmost importance for health data science.

Research topics covered by this special session include but are not limited to the following topics:

– Production of Open Data Sets
– Synthetic data sets for learning algorithm testing
– Privacy preserving machine learning, data mining and knowledge discovery
– Data leak detection
– Data citation
– Differential privacy
– Anonymization and pseudonymization
– Securing expert-in-the-loop machine learning systems
– Evaluation and benchmarking

This special session in the context of the ARES 2016 conference will bring together scientists with diverse background, interested in both the underlying theoretical principles as well as the application of such methods for practical use in the biomedical, life sciences and health care domain. The cross-domain integration and appraisal of different fields will provide an atmosphere to foster different perspectives and opinions; it will offer a platform for novel crazy ideas and a fresh look on the methodologies to put these ideas into business.

Related Resources

TIST Special Issue 2018   ACM TIST Special Issue on Advances in Causal Discovery and Inference
ECCV 2018   European Conference on Computer Vision
ICMLB 2018   International Conference on Machine Learning and Big Data 2018
ICANN 2018   27th International Conference on Artificial Neural Networks
ICML 2018   The 35th International Conference on Machine Learning
BMVC 2018   British Machine Vision Conference
MLDM 2018   14th International Conference on Machine Learning and Data Mining MLDM 2018
ACML 2018   The 10th Asian Conference on Machine Learning
COLT 2018   Computational Learning Theory
IFIP IIP 2018   10th International Conference on Intelligent Information Processing