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ILP
2007
Springer
14 years 3 months ago
Learning with Kernels and Logical Representations
In this chapter, we describe a view of statistical learning in the inductive logic programming setting based on kernel methods. The relational representation of data and background...
Paolo Frasconi
IJCAI
1989
13 years 10 months ago
An Empirical Comparison of Pattern Recognition, Neural Nets, and Machine Learning Classification Methods
Classification methods from statistical pattern recognition, neural nets, and machine learning were applied to four real-world data sets. Each of these data sets has been previous...
Sholom M. Weiss, Ioannis Kapouleas
ACSAC
1999
IEEE
14 years 2 months ago
An Application of Machine Learning to Network Intrusion Detection
Differentiating anomalous network activity from normal network traffic is difficult and tedious. A human analyst must search through vast amounts of data to find anomalous sequenc...
Chris Sinclair, Lyn Pierce, Sara Matzner
AAAI
1996
13 years 11 months ago
Formalizing Dependency Directed Backtracking and Explanation Based Learning in Refinement Search
The ideas of dependency directed backtracking (DDB) and explanation based learning (EBL) have developed independently in constraint satisfaction, planning and problem solving comm...
Subbarao Kambhampati
ICIP
2000
IEEE
14 years 11 months ago
Hierarchical Image Probability (HIP) Models
We formulate a model for probability distributions on image spaces. We show that any distribution of images can be factored exactly into conditional distributions of feature vecto...
Clay Spence, Lucas C. Parra, Paul Sajda