Bijdragen van Spid3r

8 okt 2005

• 14:468 okt 2005 14:46 wijz gesch +807 Artificial Neural Networks →* Discuss time-series prediction competitions and results obtained by neural networks.
• 14:448 okt 2005 14:44 wijz gesch +1.395 Artificial Neural Networks →* What are strong points and drawbacks for applications of neural networks to time-series prediction?
• 14:408 okt 2005 14:40 wijz gesch +253 Artificial Neural Networks →* What is a CNN template?
• 14:398 okt 2005 14:39 wijz gesch +611 Artificial Neural Networks →* What are typical application areas of cellular neural networks?
• 14:378 okt 2005 14:37 wijz gesch +2.376 Artificial Neural Networks →* Explain the problem of echo cancellation and the use of adaline networks to overcome it.
• 14:338 okt 2005 14:33 wijz gesch +11 Artificial Neural Networks →* Why does one favour small values in Bayesian learning of network weights? Explain.
• 14:338 okt 2005 14:33 wijz gesch +3.345 Artificial Neural Networks →* Explain: Bayesian learning treats the issue of model complexity differently than cross-validation does.
• 14:308 okt 2005 14:30 wijz gesch +1.485 k Artificial Neural Networks →* Explain the tiling algorithm.
• 14:308 okt 2005 14:30 wijz gesch −2 Artificial Neural Networks →* Discuss the relevance of input representation and the number of hidden units in a network construction.
• 14:308 okt 2005 14:30 wijz gesch +1.436 Artificial Neural Networks →* What is the aim of pruning and construction algorithms? Give an example.
• 14:298 okt 2005 14:29 wijz gesch +13 Artificial Neural Networks →* Discuss the relevance of input representation and the number of hidden units in a network construction.
• 14:288 okt 2005 14:28 wijz gesch +70 Artificial Neural Networks →* Are hybrid learning schemes useful? Explain with an example.
• 14:278 okt 2005 14:27 wijz gesch −55 Overleg:Artificial Neural Networks Geen bewerkingssamenvatting
• 14:278 okt 2005 14:27 wijz gesch +39 k Artificial Neural Networks →Explain the concept of energy function in neural networks?
• 14:268 okt 2005 14:26 wijz gesch +40 k Artificial Neural Networks →Is the loading capacity of the Hopfield model bounded? Explain.
• 14:258 okt 2005 14:25 wijz gesch +2.882 Artificial Neural Networks →* What sort of general tasks can one perform with unsupervised learning?
• 14:218 okt 2005 14:21 wijz gesch +15 Artificial Neural Networks →* Explain learning with a critic. Can it be applied for the control of a plant?
• 14:198 okt 2005 14:19 wijz gesch +55 Overleg:Artificial Neural Networks Geen bewerkingssamenvatting
• 14:188 okt 2005 14:18 wijz gesch +1.404 Artificial Neural Networks →* Is the loading capacity of the Hopfield model bounded? Explain.
• 14:138 okt 2005 14:13 wijz gesch −2 k Artificial Neural Networks →* Explain the concept of energy function in neural networks?
• 14:138 okt 2005 14:13 wijz gesch +1.339 Artificial Neural Networks →* Explain the concept of energy function in neural networks?
• 14:118 okt 2005 14:11 wijz gesch +30 Artificial Neural Networks →* Explain the projection method.
• 14:118 okt 2005 14:11 wijz gesch +934 Artificial Neural Networks →* How can one solve optimization problems using the Hopfield model? Give an example.
• 14:108 okt 2005 14:10 wijz gesch +3.365 Artificial Neural Networks →* What is reinforcement learning? Give some examples.
• 14:058 okt 2005 14:05 wijz gesch +11 Artificial Neural Networks →* Design a network for the weighted matching problem.
• 14:048 okt 2005 14:04 wijz gesch +149 k Artificial Neural Networks Geen bewerkingssamenvatting
• 14:018 okt 2005 14:01 wijz gesch +185 N Overleg:Artificial Neural Networks Geen bewerkingssamenvatting
• 13:598 okt 2005 13:59 wijz gesch +70 Artificial Neural Networks →Lecture 3
• 13:588 okt 2005 13:58 wijz gesch +912 Artificial Neural Networks →Explain the difference between linearly separable and linearly nonseparable tasks. Which tasks can be handled by a single layer neural network or by a multilayer neural network ?
• 13:558 okt 2005 13:55 wijz gesch +2.633 Artificial Neural Networks →What is the difference between supervised and unsupervised learning? Give examples.
• 13:538 okt 2005 13:53 wijz gesch +688 Artificial Neural Networks →Explain the difference between feedforward and recurrent nets. Give some examples.
• 13:528 okt 2005 13:52 wijz gesch +3.518 Artificial Neural Networks →Lecture 2
• 13:468 okt 2005 13:46 wijz gesch +5 k Artificial Neural Networks →3 gebieden waar ANN goed bruikbaar zijn (zie p. 21 & 22):
• 13:428 okt 2005 13:42 wijz gesch −36 k Artificial Neural Networks Geen bewerkingssamenvatting
• 13:398 okt 2005 13:39 wijz gesch +6.502 Artificial Neural Networks Geen bewerkingssamenvatting
• 13:098 okt 2005 13:09 wijz gesch +698 N Uncertainty Reasoning in Knowledge Systems Geen bewerkingssamenvatting
• 11:278 okt 2005 11:27 wijz gesch 0 Wina Examenwiki:Help Geen bewerkingssamenvatting
• 11:278 okt 2005 11:27 wijz gesch +2 Overleg Wina Examenwiki:Help Geen bewerkingssamenvatting laatste wijziging
• 11:278 okt 2005 11:27 wijz gesch +94 N Overleg Wina Examenwiki:Help Geen bewerkingssamenvatting

29 aug 2005

• 20:5329 aug 2005 20:53 wijz gesch +4 k Declaratieve Talen →Een oplossing:
• 12:4629 aug 2005 12:46 wijz gesch +41 k Declaratieve Talen →boom betegelen

24 aug 2005

• 17:0524 aug 2005 17:05 wijz gesch −1 k Declaratieve Talen →Opgave
• 17:0424 aug 2005 17:04 wijz gesch +1 k Declaratieve Talen →Opgave
• 17:0324 aug 2005 17:03 wijz gesch −1 k Declaratieve Talen →Opgave
• 17:0324 aug 2005 17:03 wijz gesch +792 Declaratieve Talen →Opgave
• 16:5524 aug 2005 16:55 wijz gesch +3.026 Declaratieve Talen →handelsreiziger verplaatsen
• 16:3724 aug 2005 16:37 wijz gesch +46 k Declaratieve Talen →Een oplossing:
• 16:3124 aug 2005 16:31 wijz gesch +278 Declaratieve Talen →Een oplossing:
• 16:2524 aug 2005 16:25 wijz gesch +924 Declaratieve Talen →Min-max
• 16:1924 aug 2005 16:19 wijz gesch +13 Declaratieve Talen →Opgave