Problemspecific neural networks, multimembered evolutionary strategy, multicriteria optimization, pruning of neural networks, damage analysis, solution of inhomogeneous linear equation systems using problemspecific neural networks Abstract The integration of neural networks and a multimembered evolutionary strategy leads to a new multicriteria optimization approach for plane truss structures. C...

Pruning, a process by which neurons selectively remove exuberant or unnecessary processes without causing cell death, is crucial for the establishment of mature neural circuits during animal development. Yet relatively little is known about molecular and cellular mechanisms that govern neuronal pruning. Holometabolous insects, such as Drosophila, undergo complete metamorphosis and their larval ...

-gram models are the most widely used language models in large vocabulary continuous speech recognition. Since the size of the model grows rapidly with respect to the model order and available training data, many methods have been proposed for pruning the least relevant -grams from the model. However, correct smoothing of the -gram probability distributions is important and performance may degr...

A natural way to deal with training samples in imbalanced class problems is to prune them removing redundant patterns, easy to classify and probably over represented, and label noisy patterns that belonging to one class are labelled as members of another. This allows classifier construction to focus on borderline patterns, likely to be the most informative ones. To appropriately define the abov...

This paper presents an efficient and robust approach for reducing the size of deep neural networks by pruning entire neurons. It exploits maxout units for combining neurons into more complex convex functions and it makes use of a local relevance measurement that ranks neurons according to their activation on the training set for pruning them. Additionally, a parameter reduction comparison betwe...

Many of the pruning strategies used to remove less likely hypotheses from the search beam in large vocabulary speech recognition (LVR) systems, have a peak search space many times greater than the average search space. This paper discusses two such pruning strategies used within BT’s speech recognition architecture [1], Step pruning and Histogram pruning. Two-tier pruning is proposed as a simpl...

There is a major research effort throughout the world to modify grapevines so that viticultural practices can be economically mechanized while maintaining or improving yield and quality. To use machines successfully for shoot positioning, pruning, harvesting, and other grape production operations, trellis systems must be devised and shoots positioned to accommodate precise mechanical movement (...

Pruning on neural networks before training not only compresses the original models, but also accelerates network phase, which has substantial application value. The current work focuses fine-grained pruning, uses metrics to calculate weight scores for screening, and extends from initial single-order pruning iterative pruning. Through these works, we argue that can be summarized as an expressive...