What determines whether points representing neurons in
1. Explain for whom, when, and why a self-learning neural network might be useful?
2. What determines whether points representing neurons in Example 10a will be blue or red?
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1 which adverse phenomena that occur during self-learning of a neural network can be eliminated by introducing
1 explain how forward contracts and options on credit default swaps are structured2 lsquolsquothe position of a buyer
describe the features of self-learning networks with very low and very high learning factor etha values do we observe
1 does valuing a cds using real-world default probabilities rather than risk-neutral default probabilities overstate or
1 explain for whom when and why a self-learning neural network might be useful2 what determines whether points
1 suppose that in a one-factor gaussian copula model the 5-year probability of default for each of 125 names is 3 and
advanced exercise design and make a model of an animal with more receptors senses to observe features of the
we can compensate for the effects of a too-large learning rate value that can risk the stability of training by
some training theories suggest that the learning rate should be small at the beginning when network makes a lot of
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