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» Learning with Globally Predictive Tests
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ILP
2001
Springer
15 years 2 months ago
Learning Functions from Imperfect Positive Data
The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
Filip Zelezný
ICML
2010
IEEE
14 years 11 months ago
Efficient Learning with Partially Observed Attributes
We describe and analyze efficient algorithms for learning a linear predictor from examples when the learner can only view a few attributes of each training example. This is the ca...
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, O...
CIKM
2005
Springer
15 years 3 months ago
Information retrieval and machine learning for probabilistic schema matching
Schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas e.g. in the data exchange domain, or for distribute...
Henrik Nottelmann, Umberto Straccia
BMCBI
2008
136views more  BMCBI 2008»
14 years 10 months ago
A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model
Background: Bioactivity profiling using high-throughput in vitro assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also r...
Richard Judson, Fathi Elloumi, R. Woodrow Setzer, ...
ICRA
2009
IEEE
188views Robotics» more  ICRA 2009»
14 years 7 months ago
Onboard contextual classification of 3-D point clouds with learned high-order Markov Random Fields
Contextual reasoning through graphical models such as Markov Random Fields often show superior performance against local classifiers in many domains. Unfortunately, this performanc...
Daniel Munoz, Nicolas Vandapel, Martial Hebert