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AI
2001
Springer
15 years 11 months ago
Learning Bayesian Belief Network Classifiers: Algorithms and System
Abstract. This paper investigates the methods for learning predictive classifiers based on Bayesian belief networks (BN) – primarily unrestricted Bayesian networks and Bayesian m...
Jie Cheng, Russell Greiner
FLAIRS
2003
15 years 8 months ago
Distributed Knowledge Representation in Neural-Symbolic Learning Systems: A Case Study
Neural-symbolic integration concerns the integration of symbolic and connectionist systems. Distributed knowledge representation is traditionally seen under a purely symbolic pers...
Artur S. d'Avila Garcez, Luís C. Lamb, Krys...
KDD
2007
ACM
149views Data Mining» more  KDD 2007»
16 years 7 months ago
Partial example acquisition in cost-sensitive learning
It is often expensive to acquire data in real-world data mining applications. Most previous data mining and machine learning research, however, assumes that a fixed set of trainin...
Victor S. Sheng, Charles X. Ling
CCS
2009
ACM
16 years 1 months ago
Active learning for network intrusion detection
Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf...
CONCUR
2010
Springer
15 years 7 months ago
Learning I/O Automata
Links are established between three widely used modeling frameworks for reactive systems: the ioco theory of Tretmans, the interface automata of De Alfaro and Henzinger, and Mealy ...
Fides Aarts, Frits W. Vaandrager