application on real-world problems at ICMLA'11 HaCDAIS 2011 The 2nd International Workshop on Handling Concept Drift in Adaptive Information Systems ICAIS 2011 Track on Incremental Learning IJCNN 2011 Special Session on Concept Drift and Learning Dynamic Environments CIDUE 2011 Symposium on Computational Intelligence in Dynamic and Uncertain Environments 2010 HaCDAIS 2010 International Workshop on Handling Concept Drift in Adaptive Information Systems: Importance, Challenges and Solutions ICMLA10 Special Session on Dynamic learning in non-stationary environments SAC 2010 Data Streams Track at ACM Symposium on Applied Computing SensorKDD 2010 International Workshop on Knowledge Discovery from Sensor Data StreamKDD 2010 Novel Data Stream Pattern Mining Techniques Concept Drift and Learning in Nonstationary Environments at IEEE World Congress on Computational Intelligence MLMDS’2010 Special Session on Machine Learning Methods for Data Streams at the 10th International Conference on Intelligent Design and Applications, ISDA’10 See also Data stream mining Data mining Machine learning Snyk, a company whose portfolio includes drift detection in software applications References Bibliographic references Many papers have been published describing algorithms for concept drift detection. Only reviews, surveys and overviews are here: Reviews Zliobaite, I., Learning under Concept Drift: an Overview. Technical Report. 2009, Faculty of Mathematics and Informatics, Vilnius University: Vilnius, Lithuania. PDF Data mining Machine learning Data analysis