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Innovations in Machine Learning : Theory and Applications
Overview
A Bayesian Approach to Causal Discovery.- A Tutorial on Learning Causal Influence.- Learning Based Programming.- N-1 Experiments Suffice to Determine the Causal Relations Among N Variables.- Support Vector Inductive Logic Programming.- Neural Probabilistic Language Models.- Computational Grammatical Inference.- On Kernel Target Alignment.- The Structure of Version Space.
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Details
- ISBN-13: 9783642067884
- ISBN-10: 3642067883
- Publisher: Springer
- Publish Date: November 2010
- Dimensions: 9.21 x 6.14 x 0.62 inches
- Shipping Weight: 0.91 pounds
- Page Count: 276
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