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MIDAA: deep archetypal analysis for interpretable multi-omic data integration based on biological principles. [PDF]
Genome BiolMilite S, Caravagna G, Sottoriva A.
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Optimizing deep belief network for concrete crack detection via a modified design of ideal gas molecular dynamics. [PDF]
Sci RepQin T +4 more
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On Practical Use of the Concept of D-Optimality
Technometrics, 1970The purpose of this article is to review the possibility of practical use of the concept of D-optimality in response surface design. Second order quasi-D-optimum designs on a cube have been built and their high efficiency proved. Using the computer, a number of different second order response surface designs, previously built, have been compared.
N. G. Mikeshina +2 more
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D-Optimality for Regression Designs: A Review
Technometrics, 1975After stating the model and the design problem, we briefly present the results for regression design prior to the work of Kiefer and Wolfowitz. We then review the major results of Kiefer and Wolfowitz, particularly those on the theory of design, as well as the way the criterion has been extended to non-linear models.
Norman R. Draper, R. C. St. John
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Training data development with the D-optimality criterion
IEEE Transactions on Neural Networks, 1999The importance of using optimum experimental design (OED) concepts when selecting data for training a neural network is highlighted in this paper. We demonstrate that an optimality criterion borrowed from another field; namely the D-optimality criterion used in OED, can be used to enhance the training value of a small training data set.
M.H. Choueiki, C.A. Mount-Campbell
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D-optimality of complete latin squares
Series Statistics, 1982Row-complete (complete) latin squares are characterized as the D-optimum designs for a linear model with row- (row- and column-) residual effects of first order.
E. Sonnemann
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Chemometrics and Intelligent Laboratory Systems, 1995
Abstract Many classical symmetrical designs have desirable characteristics, one of which is called D-optimality. The D-optimality concept can also be applied to select a design when the classical symmetrical designs cannot be used, such as when the experimental region is not regular in shape, when the number of experiments chosen by a classical ...
R. Phan-Than-Luu +4 more
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Abstract Many classical symmetrical designs have desirable characteristics, one of which is called D-optimality. The D-optimality concept can also be applied to select a design when the classical symmetrical designs cannot be used, such as when the experimental region is not regular in shape, when the number of experiments chosen by a classical ...
R. Phan-Than-Luu +4 more
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Quantitative Structure-Activity Relationships, 1993
AbstractStatistical design in principal properties based on D‐optimality criteria are particularly appropriate for selecting the most informative molecules to be synthesized and tested in the framework of QSAR studies. Selection by D‐optimal designs are better than those based on fractional factorial designs since they allow one to reduce the number of
BARONI, Massimo +4 more
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AbstractStatistical design in principal properties based on D‐optimality criteria are particularly appropriate for selecting the most informative molecules to be synthesized and tested in the framework of QSAR studies. Selection by D‐optimal designs are better than those based on fractional factorial designs since they allow one to reduce the number of
BARONI, Massimo +4 more
openaire +3 more sources