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» A statistical approach to rule learning
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128
Voted
KDD
2004
ACM
135views Data Mining» more  KDD 2004»
16 years 1 months ago
Discovering additive structure in black box functions
Many automated learning procedures lack interpretability, operating effectively as a black box: providing a prediction tool but no explanation of the underlying dynamics that driv...
Giles Hooker
115
Voted
SIGMOD
2004
ACM
184views Database» more  SIGMOD 2004»
16 years 28 days ago
CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies
The rich dependency structure found in the columns of real-world relational databases can be exploited to great advantage, but can also cause query optimizers--which usually assum...
Ihab F. Ilyas, Volker Markl, Peter J. Haas, Paul B...
105
Voted
KDD
2004
ACM
154views Data Mining» more  KDD 2004»
16 years 1 months ago
Diagnosing extrapolation: tree-based density estimation
There has historically been very little concern with extrapolation in Machine Learning, yet extrapolation can be critical to diagnose. Predictor functions are almost always learne...
Giles Hooker
BMCBI
2004
113views more  BMCBI 2004»
15 years 19 days ago
Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites
Background: Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks ...
Peter Meinicke, Maike Tech, Burkhard Morgenstern, ...
90
Voted
EKAW
2008
Springer
15 years 2 months ago
Unsupervised Discovery of Compound Entities for Relationship Extraction
In this paper we investigate unsupervised population of a biomedical ontology via information extraction from biomedical literature. Relationships in text seldom connect simple ent...
Cartic Ramakrishnan, Pablo N. Mendes, Shaojun Wang...