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...e a small cost for using a large <math> \mathbf q_{j|i} </math> to model a small <math> \mathbf p_{j|i} </math>. Therefore, the SNE cost function focuses m ...too far away in the two-dimensional map. In SNE, this will result in very small attractive force from datapoint <math> i </math> to these too-distant map p ...

...within the sphere (i.e. the data points are approximately uniform in each small local region). ...>) is to let the sphere to contain sufficiently many data points, and also small enough to satisfy the assumption that <math>\,f</math> is approximately con ...

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SSR is small and hard to recognize but contains important info with 90% accuracy. SDR is ...mask M can generate adversarial artifacts. Adversarial artifacts are very small and imperceivable by people but can ruin the classifier. This phenomenon sh ...

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...refers to instances where the gradient used in backpropagation becomes too small to make discernable differences as the parameters in the model are tuned, a ...epth, it becomes more difficult to train them as gradients may become very small. The authors developed a method that train a model to fit a residual mappin ...

...m of the weights equal to N. Analogous to <math>\beta</math> distribution, small <math>a</math> allows the model to up- or down-scale weights <math>\boldsym ...on at z affects the statistic T(F). Thus, this corrupted z value will have small effect on the statistic T(F). ...

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...ed for parameter and model selection. Second, regarding the selection of a small representative subgraph as training set, a method based on Expansion factor 6). Repeat the above procedure untill change in EF value is too small (comparing to a threshold specified by the user) ...