Results 251 to 260 of about 379,530 (310)
Caveats on Using Firth's Penalization in the Model-Based Regression Standardization for Rare Diseases. [PDF]
Stat MedHashibe S, Hongo W, Shinozaki T.
europepmc +1 more source
Feed-forward neural networks for genomic selection: insights into varying levels of dominance heritability. [PDF]
BMC GenomicsSahebalam H, Gholizadeh M.
europepmc +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Optimization on parametric model
NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium, 2018Neural networks are both computationally intensive and memory intensive, making them difficult to deploy on embedded systems with large number of weights consume considerable storage and memory bandwidth. To address this limitation, pruning is an effective way to compress neural networks with high accuracy.
Fenfen Huang, Wenbin Yao
openaire +1 more source
Neuro-wavelet parametric modeling
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium, 2000This work describes Neuro-Wavelet Parametric Modeling, a neural-based technique to classify, model and forecast signals or problems which are functions of either time or space. The paper presents the base method and discusses on the selection of the optimal neuro-wavelet network. An industrial application is also presented.
COLLA, Valentina +2 more
openaire +4 more sources
Identification in Parametric Models
Econometrica, 1971A theory of identification is developed for a general stochastic model whose probability law is determined by a finite number of parameters. It is shown under weak regularity conditions that local identifiability of the unknown parameter vector is equivalent to nonsingularity of the information matrix.
openaire +2 more sources
Journal of Electronic Testing, 1995
Assuming that the distribution of path delays introduced by variations in the manufacturing process is exponential instead of gaussian, the interdependence problem between delay-optimization of synthesized networks and parametric yield has been revisited. The result confirms the claim of Williams, Underwood, and Mercer.
openaire +1 more source
Assuming that the distribution of path delays introduced by variations in the manufacturing process is exponential instead of gaussian, the interdependence problem between delay-optimization of synthesized networks and parametric yield has been revisited. The result confirms the claim of Williams, Underwood, and Mercer.
openaire +1 more source
Studies in health technology and informatics, 2007
The shape of anatomic objects often depends in complex ways on the shapes and locations of neighboring objects. Shape parameter networks provide an approach for representing shape dependencies and producing multi-object models that share consistent boundary definitions.
Jessica R. Crouch, Andrew Cherry
openaire +2 more sources
The shape of anatomic objects often depends in complex ways on the shapes and locations of neighboring objects. Shape parameter networks provide an approach for representing shape dependencies and producing multi-object models that share consistent boundary definitions.
Jessica R. Crouch, Andrew Cherry
openaire +2 more sources
A modeling paradigm incorporating parametric and non-parametric methods
The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2005A novel parametric/non-parametric modeling paradigm was defined and used in characterization of synaptic transmission. In this paradigm, parametric and nonparametric techniques were incorporated in a complementary manner. Non-parametric method was used to generalize experimental data and extract system input/output properties.
D, Song +3 more
openaire +2 more sources