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Surrogate Network-Based Sparseness Hyper-Parameter Optimization for Deep Expression Recognition
Pattern Recognition, 2021For facial expression recognition, the sparseness constraints of the features or weights can improve the generalization ability of a deep network. However, the optimization of the hyper-parameters in fusing different sparseness strategies demands much ...
Weicheng Xie, Linlin Shen, Wenting Chen
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International audienceIt is widely recognized that the performances of frequent-pattern mining algorithms are closely dependent on data being handled, i.e., sparse or dense.
S Ben Yahia
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Sparseness Analysis in the Pretraining of Deep Neural Networks
IEEE Transactions on Neural Networks and Learning Systems, 2017Jun Li, Xiao-Tong Yuan, Jian Yang
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Sparseness-Controlled Proportionate Affine Projection Sign Algorithms for Acoustic Echo Cancellation
Circuits, Systems, and Signal Processing, 2015Badong Chen, Yi Yu
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Reconstructing Spatially Extended Brain Sources via Enforcing Multiple Transform Sparseness
NeuroImage, 2014Lei Ding, Min Zhu
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, 2020
While the theory of Bayesian system identification provides a probabilistic means for reliably and robustly inferring models of a dynamic system and their parameters based on measured dynamic response, exploiting sparseness during online tracking of ...
Yong Huang +4 more
semanticscholar +1 more source
While the theory of Bayesian system identification provides a probabilistic means for reliably and robustly inferring models of a dynamic system and their parameters based on measured dynamic response, exploiting sparseness during online tracking of ...
Yong Huang +4 more
semanticscholar +1 more source
Minimizing Energy by Achieving Optimal Sparseness in Parallel Adders
IEEE Symposium on Computer Arithmetic, 2015Vojin G. Oklobdzija
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