Levine et al., 2016 - Google Patents
End-to-end training of deep visuomotor policiesLevine et al., 2016
View PDF- Document ID
- 4721631804326015979
- Author
- Levine S
- Finn C
- Darrell T
- Abbeel P
- Publication year
- Publication venue
- Journal of Machine Learning Research
External Links
Snippet
For spline regressions, it is well known that the choice of knots is crucial for the performance of the estimator. As a general learning framework covering the smoothing splines, learning in a Reproducing Kernel Hilbert Space (RKHS) has a similar issue. However, the selection …
- 230000001537 neural 0 abstract description 32
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
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