posted by organizer: Aholzinger || 5110 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

SI-FDS-MLJ 2021   CFP: Special Issue on Foundations of Data Science - Machine Learning Journal
ICDM 2020   20th IEEE International Conference on Data Mining
Recommender systems 2020   Scopus/Springer Special issue: Data Science for Next-Generation Recommender Systems with International Journal of Data Science and Analytics
IEEE COINS 2020   Internet of Things IoT | Artificial Intelligence | Machine Learning | Big Data | Blockchain | Edge & Cloud Computing | Security | Embedded Systems | Circuit and Systems | WSN | 5G
NeuRec 2020   ICDM Workshop on Recommender Systems 2020
MNLP 2020   4th IEEE Conference on Machine Learning and Natural Language Processing
IEEE-CVIV 2020   2020 2nd International Conference on Advances in Computer Vision, Image and Virtualization (CVIV 2020)
WSPML 2020   2020 2nd International Workshop on Signal Processing and Machine Learning (WSPML 2020)
ICMBWA 2020   International Conference on Managing Business through Web Analytics
AICA 2020   O'Reilly AI Conference San Jose