Results 271 to 280 of about 57,263 (295)

A Non-Equidistant Elastic Net Algorithm

1997
The statistical mechanical derivation by Simic of the Elastic Net Algorithm (ENA) from a stochastic Hopfield neural network is criticized. In our view, the ENA should be considered a dynamic penalty method. Using a linear distance measure, a Non-equidistant Elastic Net Algorithm (NENA) is presented.
van den Berg, J (Jan), Geselschap, JH
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Robust Elastic-Net Subspace Representation

IEEE Transactions on Image Processing, 2016
Recently, finding the low-dimensional structure of high-dimensional data has gained much attention. Given a set of data points sampled from a single subspace or a union of subspaces, the goal is to learn or capture the underlying subspace structure of the data set.
Eunwoo Kim, Minsik Lee 0001, Songhwai Oh
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Elastic net for paralinguistic speech recognition

Proceedings of the 14th ACM international conference on Multimodal interaction, 2012
Given the fact that the length of the feature vector that is being used for the paralinguistic recognition of speech has exceeded some thousands, the importance of a sparse representation of a model becomes notable. The importance of a sparse representation is mainly due to the more interpretability, higher generalization capability, and numerically ...
Pouria Fewzee 0001, Fakhri Karray
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Topology-Preserving Elastic Nets

2001
We have developed a topology-preserving elastic net which combines both lateral and synaptic interactions to obtain topologically ordered representations (receptive fields) of an external stimulus. Existing neural models that preserve the topology by utilizing lateral interactions, such as the Kohonen map and Goodhill's mapping, and by utilizing ...
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Operational issues of sequencing with elastic nets

Artificial Intelligence in Engineering, 2000
Abstract The usefulness of the elastic net (EN) approach for the general sequencing problem is investigated. Initial parameter setting and subsequent adjustments need to be intelligently undertaken for various applications. Based on the experiments on the typical traveling salesman problem, helpful guidelines were suggested.
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Time elastic digital systems and Petri Nets

2008 8th International Conference on Application of Concurrency to System Design, 2008
Summary form only given. Digital electronic systems typically uses synchronous clocks and primarily assume fixed duration of their operations to simplify the design process. Time elastic systems can be constructed either by replacing the clock with communication handshakes (asynchronous version) or by augmenting the clock with a synchronous version of ...
Michael Kishinevsky, Jordi Cortadella
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A robust elastic net approach for feature learning

Journal of Visual Communication and Image Representation, 2014
Unsupervised feature learning has drawn more and more attention especially in visual representation in past years. Traditional feature learning approaches assume that there are few noises in training data set, and the number of samples is enough compared with the dimensions of samples.
Ling Wang 0013, Hong Cheng 0002, Zicheng Liu 0001, Ce Zhu   +3 more
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On grouping effect of elastic net

Statistics & Probability Letters, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Elastic nets, travelling salesmen and cortical maps

Current Biology, 1992
Hubel and Wiesel [ 1 ] were the first to show that many neuronal response properties vary systematically with position on the surface of the primate visual cortex. Not 0nly are these so-called maps highly ordered, but recent results obtained by direct imaging of neuronal activity patterns with voltage-sensitive dyes [2,3], have shown that the different
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Bayesian Elastic Net Tobit Quantile Regression

Communications in Statistics - Simulation and Computation, 2014
In this article, the problem of parameter estimation and variable selection in the Tobit quantile regression model is considered. A Tobit quantile regression with the elastic net penalty from a Bayesian perspective is proposed. Independent gamma priors are put on the l1 norm penalty parameters.
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