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Artificial Neural Networks (ANNs) have emerged as hot topics in the research community.
Intrinsically sparse long short-term memory networks
Liu, S., Mocanu, D. C., and Pechenizkiy, M · 1901
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On random graphs i
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Learning representations by back-propagating errors
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A back-propagation algorithm with optimal use of hidden units
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Optimal brain damage
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Eshelman, L. J · 1991
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Langley, P · 1994
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Exploring complex networks
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Distributional word clusters vs. words for text categorization
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Overfitting in making comparisons between variable selection methods
Reunanen, J · 2003
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Pitfalls in the use of dna microarray data for diagnostic and prognostic classification
Simon, R., Radmacher, M. D., Dobbin, K., and McShane, L. M · 2003
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Gene expression profiling of gliomas strongly predicts survival
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Microarray gene expression profiling of b-cell chronic lymphocytic leukemia subgroups defined by genomic aberrations and vh mutation status
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Feature-based image registration by means of the chc evolutionary algorithm
Cordón, O., Damas, S., and Santamaría, J · 2006
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Feature selection with a perceptron neural net
Mejía-Lavalle, M., Sucar, E., and Arroyo, G · 2006
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Distributed computation of the knn graph for large high-dimensional point sets
Plaku, E. and Kavraki, L. E · 2007
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Mapreduce: simplified data processing on large clusters
Dean, J. and Ghemawat, S · 2008
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Performing feature selection with multilayer perceptrons
Romero, E. and Sopena, J. M · 2008
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Sofmls: online self-organizing fuzzy modified least-squares network
de Jesús Rubio, J · 2009
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Destrero, A., Mosci, S., De Mol, C., Verri, A., and Odone, F · 2009
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The weka data mining software: an update
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Mundra, P. A. and Rajapakse, J. C · 2009
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de Jesús Rubio, J · 2017
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In-datacenter performance analysis of a tensor processing unit
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Learning sparse neural networks through l _ 0 l\_0 regularization
Louizos, C., Welling, M., and Kingma, D. P · 2017
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Deep learning in bioinformatics
Min, S., Lee, B., and Yoon, S · 2017
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Feature selection for steganalysis using the mahalanobis distance
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Clinical utility of microarray-based gene expression profiling in the diagnosis and subclassification of leukemia: report from the international microarray innovations in leukemia study group
Haferlach, T., Kohlmann, A., Wieczorek, L., Basso, G., Kronnie, G. T., Béné, M.-C., De, J. V., Hernández, J. M., Hofmann, W.-K., Mills, K. I., et al · 2010
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Advancing feature selection research
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Fast wrapper feature subset selection in high-dimensional datasets by means of filter re-ranking
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Improving neural networks by preventing co-adaptation of feature detectors
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Using deep learning to enhance cancer diagnosis and classification
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Exploring sparsity in recurrent neural networks
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Soft weight-sharing for neural network compression
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Learning intrinsic sparse structures within long short-term memory
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Lifelong learning with dynamically expandable networks
Yoon, J., Yang, E., Lee, J., and Hwang, S. J · 2017
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The lottery ticket hypothesis: Finding sparse, trainable neural networks
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On the estimation and control of nonlinear systems with parametric uncertainties and noisy outputs
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Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science
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