posted by user: xukevin || 3608 views || tracked by 14 users: [display]

BMAW 2012 : The 9th Bayesian Modelling Applications Workshop


When Aug 18, 2012 - Aug 18, 2012
Where Catalina Island, California, USA
Abstract Registration Due May 1, 2012
Submission Deadline May 5, 2012
Notification Due Jun 11, 2012
Final Version Due Jul 31, 2012
Categories    machine learning   artificial intelligence   signal processing   modeling

Call For Papers

UAI 9th Bayesian Modeling Applications Workshop
Call for Papers
Saturday, August 18th, 2012
Catalina Island, California, USA.

Special theme: Temporal Modeling

The 9th Bayesian Modeling Applications Workshop solicits submissions of real-world applications of graphical models and Bayesian networks,in particular those dealing with temporal modeling. Our desire is to foster discussion and interchange about novel contributions that can speak to both the academic and the larger research community. Accordingly, we seek submissions also from practitioners and tool developers as well as researchers.

Bayesian networks are now a powerful, well-established technology for reasoning under uncertainty, supported by a wide range of mature academic and commercial software tools. They are now being applied in many domains, including environmental and ecological modeling, bioinformatics, medical decision support, many types of engineering, robotics, military, financial and economic modeling, education, forensics, emergency response, surveillance, and so on. We welcome submissions describing such real world applications, whether as stand-alone BNs or where the BNs are embedded in a larger software system. We encourage authors to address the practical issues involved in developing real-world applications, such as knowledge engineering methodologies, elicitation techniques, defining and meeting client needs, validation processes and integration methods, as well as software tools to these support these activities.

We particularly encourage the submission of papers that address the workshop theme of temporal modeling. Recently communities building dynamic Bayes networks (DBNs) and partially observable MDPs (POMDPs) are coming to realize that they are applying their methods to identical applications. Similarly POMDPs and other probabilistic methods are now established in the field of Automated Planning. Stochastic process models such as continuous time Bayes networks (CTBNs) should also be considered as part of this trend. Adaptive and on-line learning models also fit into this focus.

Related Resources

IPMU 2020   18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems
ICDM 2020   20th IEEE International Conference on Data Mining
ICMLA 2020   International Conference on Machine Learning and Applications
IEEE-CVIV 2020   2020 2nd International Conference on Advances in Computer Vision, Image and Virtualization (CVIV 2020)
CHIL 2020   ACM Conference on Health, Inference, and Learning
EMNLP 2020   Conference on Empirical Methods in Natural Language Processing
BDTA 2020   10th EAI International Conference on Big Data Technologies and Applications
ACM--ICMLC--Ei and Scopus 2020   ACM--2020 12th International Conference on Machine Learning and Computing (ICMLC 2020)--SCOPUS, Ei Compendex
ICARA--IEEE, Ei, Scopus 2021   IEEE--2020 7th International Conference on Automation, Robotics and Applications (ICARA 2020)--Ei Compendex, Scopus
ICANN 2020   29th International Conference on Artificial Neural Networks