Learning time-varying concepts

On the complexity of learning from drifting distributions

COLT '96 Proceedings of the ninth annual conference on Computational learning theory

Tolerating Concept and Sampling Shift in Lazy Learning UsingPrediction Error Context Switching

Artificial Intelligence Review - Special issue on lazy learning

The complexity of learning according to two models of a drifting environment

COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory

The Complexity of Learning According to Two Models of a Drifting Environment

Machine Learning - The Eleventh Annual Conference on computational Learning Theory

Tracking Linear-Threshold Concepts with Winnow

COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory

Distinctive Features of Minimization of a Risk Functional in Mass Data Sets

Cybernetics and Systems Analysis

Tracking linear-threshold concepts with Winnow

The Journal of Machine Learning Research

Applying lazy learning algorithms to tackle concept drift in spam filtering

Expert Systems with Applications: An International Journal

PointMap: A Real-Time Memory-Based Learning System with On-line and Post-Training Pruning

International Journal of Hybrid Intelligent Systems

Learning drifting concepts: Example selection vs. example weighting

Intelligent Data Analysis

Boosting classifiers for drifting concepts

Intelligent Data Analysis - Knowlegde Discovery from Data Streams

Local likelihood modeling of temporal text streams

Proceedings of the 25th international conference on Machine learning

Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts

The Journal of Machine Learning Research

An Efficient and Sensitive Decision Tree Approach to Mining Concept-Drifting Data Streams

Informatica

Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams

Proceedings of the 2010 conference on Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams

On-line learning with delayed label feedback

ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory

SRF: a framework for the study of classifier behavior under training set mislabeling noise

PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I

Tracking concept drift in malware families

Proceedings of the 5th ACM workshop on Security and artificial intelligence

On evaluating stream learning algorithms

Machine Learning