Reference : Human in the Loop: Interactive Passive Automata Learning via Evidence-Driven State-Me...
Scientific congresses, symposiums and conference proceedings : Poster
Engineering, computing & technology : Computer science
Computational Sciences
http://hdl.handle.net/10993/32815
Human in the Loop: Interactive Passive Automata Learning via Evidence-Driven State-Merging Algorithms
English
Hammerschmidt, Christian mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) >]
State, Radu mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) >]
Verwer, Sicco [Delft University of Technology - TU Delft > Cyber Security Group]
Aug-2017
Yes
International
Human in the Loop Machine Learning Workshop at the International Conference on Machine Learning
August 11th
Sydney
Australia
[en] Computer Science - Learning ; Statistics - Machine Learning
[en] We present an interactive version of an evidence-driven state-merging (EDSM) algorithm for learning variants of finite state automata. Learning these automata often amounts to recovering or reverse engineering the model generating the data despite noisy, incomplete, or imperfectly sampled data sources rather than optimizing a purely numeric target function. Domain expertise and human knowledge about the target domain can guide this process, and typically is captured in parameter settings. Often, domain expertise is subconscious and not expressed explicitly. Directly interacting with the learning algorithm makes it easier to utilize this knowledge effectively.
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/32815
http://arxiv.org/abs/1707.09430
arXiv: 1707.09430
FnR ; FNR10053360 > Christian Hammerschmidt > PAULINE > Stream Mining For Predictive Authentication Under Adversarial Influence > 01/03/2015 > 14/11/2017 > 2015

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