IEEE Transactions on Software Engineering - Special issue on computer security and privacy
A Method for Attribute Selection in Inductive Learning Systems
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Incremental learning of concept descriptions: A method and experimental results
Machine intelligence 11
Computer-Access Security Systems Using Keystroke Dynamics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Instance-Based Learning Algorithms
Machine Learning
Redundant noisy attributes, attribute errors, and linear-threshold learning using winnow
COLT '91 Proceedings of the fourth annual workshop on Computational learning theory
A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Forgetting and aging of knowledge in concept formation
Applied Artificial Intelligence
C4.5: programs for machine learning
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The weighted majority algorithm
Information and Computation
Learning in the presence of concept drift and hidden contexts
Machine Learning
A hybrid conceptual clustering system
CSC '96 Proceedings of the 1996 ACM 24th annual conference on Computer science
Tracking Context Changes through Meta-Learning
Machine Learning - Special issue on multistrategy learning
Selective Sampling Using the Query by Committee Algorithm
Machine Learning
Progressive partial memory learning
Progressive partial memory learning
Decision Tree Induction Based on Efficient Tree Restructuring
Machine Learning
Handling concept drifts in incremental learning with support vector machines
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
The application of AdaBoost for distributed, scalable and on-line learning
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Selective sampling for nearest neighbor classifiers
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Temporal sequence learning and data reduction for anomaly detection
ACM Transactions on Information and System Security (TISSEC)
ACM Computing Surveys (CSUR)
Mining high-speed data streams
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
IEEE Transactions on Pattern Analysis and Machine Intelligence
Selecting Examples for Partial Memory Learning
Machine Learning
The 1999 DARPA off-line intrusion detection evaluation
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue on recent advances in intrusion detection systems
Probabilistic Models of Appearance for 3-D Object Recognition
International Journal of Computer Vision
Adaptive Intrusion Detection: A Data Mining Approach
Artificial Intelligence Review - Issues on the application of data mining
Incremental clustering for profile maintenance in information gathering web agents
Proceedings of the fifth international conference on Autonomous agents
Mining time-changing data streams
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Essential System Administration, Second Edition
Essential System Administration, Second Edition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
An Initial Study of an Adaptive Hierarchical Vision System
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Image Color Constancy Using EM and Cached Statistics
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
A Brief Introduction to Boosting
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Incremental Learning with Partial Instance Memory
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Selective Sampling with Redundant Views
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
A Method for Partial-Memory Incremental Learning and its Application to Computer Intrusion Detection
TAI '95 Proceedings of the Seventh International Conference on Tools with Artificial Intelligence
Generalizing over Aspect and Location for Rooftop Detection
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Learning Based Interactive Image Segmentation
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Incremental rule learning based on example nearness from numerical data streams
Proceedings of the 2005 ACM symposium on Applied computing
Data streams classification by incremental rule learning with parameterized generalization
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Using classifier ensembles to label spatially disjoint data
Information Fusion
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Efficient instance-based learning on data streams
Intelligent Data Analysis
Learning in Environments with Unknown Dynamics: Towards more Robust Concept Learners
The Journal of Machine Learning Research
Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts
The Journal of Machine Learning Research
Language Acquisition: The Emergence of Words from Multimodal Input
TSD '08 Proceedings of the 11th international conference on Text, Speech and Dialogue
Using Data Mining Algorithms for Statistical Learning of a Software Agent
KES-AMSTA '07 Proceedings of the 1st KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
A Computational Model of Language Acquisition: the Emergence of Words
Fundamenta Informaticae - Cognitive Informatics, Cognitive Computing, and Their Denotational Mathematical Foundations (I)
Active learning with near misses
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
IEEE Transactions on Neural Networks
An ensemble approach for incremental learning in nonstationary environments
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Conflict-free incremental learning
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Detecting and ordering salient regions
Data Mining and Knowledge Discovery
Incremental learning by heterogeneous bagging ensemble
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
Journal of Biomedical Informatics
Adaptive classifier selection based on two level hypothesis tests for incremental learning
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Detecting change via competence model
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
Very Fast Decision Rules for multi-class problems
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Learning decision rules from data streams
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
A Computational Model of Language Acquisition: the Emergence of Words
Fundamenta Informaticae - Cognitive Informatics, Cognitive Computing, and Their Denotational Mathematical Foundations (I)
Active learning of relational action models
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
An attempt to employ genetic fuzzy systems to predict from a data stream of premises transactions
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
Handling time changing data with adaptive very fast decision rules
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
An analysis of change trends by predicting from a data stream using genetic fuzzy systems
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part I
Information Sciences: an International Journal
A survey on concept drift adaptation
ACM Computing Surveys (CSUR)
Concept drift detection via competence models
Artificial Intelligence
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Agents that learn on-line with partial instance memory reserve some of the previously encountered examples for use in future training episodes. In earlier work, we selected extreme examples--those from the boundaries of induced concept descriptions--combined these with incoming instances, and used a batch learning algorithms to generate new concept descriptions. In this paper, we extend this work by combining our method for selecting extreme examples with two incremental learning algorithms, AQ11 and GEM. Using these new systems, AQ11-PM and GEM-PM, and using two real-world applications, those of computer intrusion detection and blasting cap detection in X-ray images, we conducted a lesion study to analyze the trade-offs between predictive accuracy, examples held in memory, learning time, and concept complexity. Empirical results showed that although the use of our partial-memory model did decrease predictive accuracy when compared to systems that learn from all available training data, it also decreased memory requirements, decreased learning time, and in some cases, decreased concept complexity. We also present results from an experiment using the STAGGER Concepts, a synthetic data set involving concept drift, suggesting that our methods perform comparably to the FLORA2 system in terms of predictive accuracy, but store fewer examples. Moreover, these outcomes are consistent with earlier results using our partial-memory model and batch learning.