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Published in 2020 at "Pattern Analysis and Applications"
DOI: 10.1007/s10044-020-00867-8
Abstract: One of the crucial problems of designing a classifier ensemble is the proper choice of the base classifier line-up. Basically, such an ensemble is formed on the basis of individual classifiers, which are trained in…
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Keywords:
pruning algorithms;
novel clustering;
based pruning;
clustering based ... See more keywords
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Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3184730
Abstract: A recurrent neural network (RNN) has shown powerful performance in tackling various natural language processing (NLP) tasks, resulting in numerous powerful models containing both RNN neurons and feedforward neurons. On the other hand, the deep…
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Keywords:
neural networks;
recurrent neural;
based pruning;
stage wise ... See more keywords
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Published in 2023 at "Scientific Programming"
DOI: 10.1155/2023/9983781
Abstract: Convolutional neural networks (CNNs) have shown their great power in multiple computer vision tasks. However, many recent works improve their performance by adding more layers and parameters, which lead to computational redundancy in many application…
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Keywords:
neural network;
network based;
based pruning;
structured pruning ... See more keywords
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Published in 2022 at "Applied Intelligence"
DOI: 10.48550/arxiv.2204.04977
Abstract: Deep neural networks exploiting million parameters are currently the norm. This is a potential issue because of the great number of computations needed for training, and the possible loss of generalization performance of overparameterized networks.…
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Keywords:
pruning irrelevant;
deep neural;
regularization;
based pruning ... See more keywords