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...p state-action pairs. The disadvantage of BC is that the training requires large amounts of expert data, which is hard to obtain. In addition, an agent trai ...es each action since the transition function to move from state A to state B is not learned. ...

[[File:Det_vs_sto.jpg]] ...itial position and pattern starts to repeat, but if we make the number set large enough we can prevent the numbers from repeating too early. Although the ps ...

...ntensive studies of methods using AI to search for the optimal solution of large-scale, zero-sum and extensive form problems. However, most of these works o ...ors found that the best way to implement the module was to use a medium to large batch size, RMSProp, or Adam optimizers with a learning rate between <math> ...

...le, despite these, BNNs do not scale to the state of the art techniques or large data sets. There are techniques to explicitly avoid modeling the full weigh ...single beset configuration (one-hot encoding). Specifically, BNNs with the Gaussian Weight prior $$F_x(y) = N (0,T^{-1} I)$$ has score of configuration <math>W ...

...ve Congruential Method'''. This involves three integer parameters ''a'', ''b'', and ''m'', and a '''seed''' variable ''x₀''. This method dete :<math>x_{i+1} = (ax_{i} + b) \mod{m}</math> ...

# It has a saturation region, so it can dampen variances that are too large; ...e number of nodes is common, so <math display="inline">n</math> is usually large, and by the Central Limit Theorem, <math display="inline">z</math> approach ...

Image:Numerical example of PCA.jpg|Finding two principal components of original data in 2D space. Components o ...en reconstruct the picture using first d principal components. If d is too large, we can not completely remove the noise. If it is too small, we will lose s ...

Also let <math>B = \{2\},\ X_B = \{X_2\}</math> so we can write <math>A \longrightarrow B</math>: <math>A\,\!</math> "causes" <math>B\,\!</math>. ...

...an take and/or the number of possible game states is finite. Deep CNNs for large, non-convex continuous action spaces are not directly applicable. To solve ...s chosen as a domain to test the network on. Curling was chosen due to its large action space, the potential for complicated strategies, and the need for pr ...

...assic Machine Learning techniques such as k-nearest neighbors (KNNs) [15], Gaussian Processes [16], and Support Vector Machines [17]. However, these models wer ...y-based methods have a deficiency of getting lower accuracies when shown a large open area in the images as mentioned by the authors. The authors put forth ...

...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 ...