The Prism family of algorithms induces modular classification rules in contrast to the Top Down Induction of Decision Trees (TDIDT) approach which induces classification rules in the intermediate form of a tree structure. Both approaches achieve a comparable classification accuracy. However in some cases Prism outperforms TDIDT. For both approaches pre-pruning facilities have been developed in ...

In this paper, we solve the sum mean-squared error (MSE)optimal 1-bit quantized precoding problem exactly for smallto-moderate sized multiuser multiple-input multiple-output (MU-MIMO) systems via branch and bound. To this end, we reformulate the original NP-hard precoding problem as a tree search and deploy a number of strategies that improve the pruning efficiency without sacrificing optimalit...

Axon pruning is widely used for the refinement of neural circuits in both vertebrates and invertebrates, and may also contribute to the pathogenesis of neurodegenerative diseases. However, little is known about the cellular and molecular mechanisms of axon pruning. We use the stereotyped pruning of gamma neurons of the Drosophila mushroom bodies (MB) during metamorphosis to investigate these me...

This paper presents a new pruning method to determine a nearly optimum multi-layer neural network structure. The aim of the proposed method is to reduce the size of the network by freezing any node that does not actively participate in the training process. A node is not active if it has little or no effect to reduce the error of the network as the training proceeds. Experimental results demons...

Selective degeneration of neuronal projections and neurite pruning are critical for establishment and maintenance of functional neural circuits in both insects and mammals. However, the molecular mechanisms that govern developmental neurite pruning versus injury-induced neurite degeneration are still mostly unclear. Here, we show that the effector caspases 6 and 3 are both expressed within axon...

Large-scale real-world graphs are known to have highly skewed vertex degree distribution and highly skewed edge weight distribution. Existing vertex-centric iterative graph computation models suffer from a number of serious problems: (1) poor performance of parallel execution due to inherent workload imbalance at vertex level; (2) inefficient CPU resource utilization due to short execution time...

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...