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...bandwidth parameter $b$. That is: $k(z, z') = \exp(-||vec(z) - vec(z')||^2/b)$. ...tance $\mathbf{A} \to \mathbf{C}$), where the source-domain discrepancy is large. The authors take this to mean that the proposed model learns "more adaptiv ...

[[File:裁剪.jpg]]<br /> ...his is a linear function in <math>\ x </math> with general form <math>\,ax+b=0</math>. ...

...kes raw pixels as input and maps them to values or actions. As a drawback, large amounts of training data is required. In addition, the policies are not gen ...n(2011)]]] try to capture model uncertainty by applying high-computational Gaussian Process models. In order to develop such a policy search method, the author ...

...) and assume a parametric model for densities. Assume class conditional is Gaussian. 1) Assume Gaussian distributions ...

...using machine learning is how to efficiently find useful patterns in very large amounts of data. An interesting quote that describes this problem quite wel ...nt classification techniques can be very useful for data mining using very large data sets. This is most useful when the structure of the data is not well u ...