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IDA
2007
Springer
14 years 1 months ago
Combining Bagging and Random Subspaces to Create Better Ensembles
Random forests are one of the best performing methods for constructing ensembles. They derive their strength from two aspects: using random subsamples of the training data (as in b...
Pance Panov, Saso Dzeroski
ICML
1996
IEEE
13 years 11 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
KBSE
2000
IEEE
14 years 1 days ago
Practical Large Scale What-If Queries: Case Studies with Software Risk Assessment
When a lack of data inhibits decision making, large scale what-if queries can be conducted over the uncertain parameter ranges. Such what-if queries can generate an overwhelming a...
Tim Menzies, Erik Sinsel
PAMI
2000
113views more  PAMI 2000»
13 years 7 months ago
Hierarchical Discriminant Regression
This paper presents a new technique which incrementally builds a hierarchical discriminant regression (IHDR) tree for generation of motion based robot reactions. The robot learned...
Wey-Shiuan Hwang, Juyang Weng
JMLR
2006
132views more  JMLR 2006»
13 years 7 months ago
Learning to Detect and Classify Malicious Executables in the Wild
We describe the use of machine learning and data mining to detect and classify malicious executables as they appear in the wild. We gathered 1,971 benign and 1,651 malicious execu...
Jeremy Z. Kolter, Marcus A. Maloof