Robustness
Data (the sample) contains all the information from which various conclusions will be drawn about the process that generated them. A major concern of Data Modeling is then to assess the credibility of these conclusions.
Robustness -- Neural networks tend to tolerate noisy input and behave appropriately in new situations.
[edit] Robustness
If intervals are incorrect (in the sense that the game-theoretic value of the node is not contained within the interval), then B* might not be able to identify the correct path.
Robustness of efficiency refers to high effectiveness in the face of non-normal tails. That is, confidence intervals for the population location tend to be almost as narrow as the best that could be done if we knew the true shape of the distributuion.
Adaptibility, robustness, broad-spectrum intelligence, understandability, self-repair... Much the same reasons as the Military still finds a use for soldiers! ...
goal neglect and attentional lapses work better for me than neural noise and "robustness of bindings".
"The use of multiple mobile robots offers significant advantages over the use of single mobile robots: key features are the possibility of distributed sensing, distributed action, task dependent reconfigurability, and the enabling of robustness and ...
Not much is known about the robustness of Wilks' lambda to violations of this assumption.
Bootstrapping A technique for simulating new data sets, to assess the robustness of a model or to produce a set of likely models.
8 Regression: Robustness Considerations 289
6.9 Optimal Solution of the Linear Regression Problem 293
6.10 The Representer Theorem and Related Issues 296
6.11 Summary and Discussion 302
Notes and References 304
Problems 307 ...
bulky in size, sophisticated in complexity, and tend to originate from the integration of
multiple components developed by different software teams, it is an increasingly challenging
task to ensure software robustness and reliability.
 See also: Distribution, Artificial intelligence, Neural network, Knowledge, Complexity
  
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