Results 241 to 250 of about 2,081,128 (286)

Heterogeneous Domain Adaptation via Nonlinear Matrix Factorization

IEEE Transactions on Neural Networks and Learning Systems, 2020
Heterogeneous domain adaptation (HDA) aims to solve the learning problems where the source- and the target-domain data are represented by heterogeneous types of features. The existing HDA approaches based on matrix completion or matrix factorization have proven to be effective to capture shareable information between heterogeneous domains.
Haoliang Li, Sinno Jialin Pan, Shiqi Wang, Alex C. Kot   +3 more
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Beyond cross-domain learning: Multiple-domain nonnegative matrix factorization

Engineering Applications of Artificial Intelligence, 2014
Traditional cross-domain learning methods transfer learning from a source domain to a target domain. In this paper, we propose the multiple-domain learning problem for several equally treated domains. The multiple-domain learning problem assumes that samples from different domains have different distributions, but share the same feature and class label
Wang, Jim Jing-Yan, Gao, Xin
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Domain structure and organisation in extracellular matrix proteins

Matrix Biology, 2002
Extracellular matrix (ECM) proteins are large modular molecules built up from a limited set of modules, or domains. The basic folds of many domains have now been determined by crystallography or NMR spectroscopy. Recent structures of domain pairs and larger tandem arrays, as well as of oligomerisation domains, have begun to reveal the principles ...
Erhard, Hohenester, Jürgen, Engel
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On Non-Distinguished Matrix Domains

Results in Mathematics, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Díaz, Juan Carlos, Grosse-Erdmann, Karl-Goswin   +1 more
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Operators Between Matrix Domains

2021
In this chapter, we apply the results of the previous chapters to characterize matrix transformations on the spaces of generalized weighted means and on matrix domains of triangles in BK spaces. We also establish estimates or identities for the Hausdorff measure of noncompactness of matrix transformations from arbitrary BK spaces with AK into c, \(c_{0}
Bruno de Malafosse, Eberhard Malkowsky, Vladimir Rakočević   +2 more
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On matrix domains of triangles

Applied Mathematics and Computation, 2007
The authors' summary clearly explains the content of this paper: ``We prove some general results for the determination of the \(\beta \)-duals of, and the characterisations of matrix transformations on matrix domains of arbitrary triangles in FK-spaces. Our results contain almost all recently published ones as special cases.
Malkowsky, Eberhard, Rakočević, Vladimir   +1 more
openaire   +1 more source

Domain transfer nonnegative matrix factorization

2014 International Joint Conference on Neural Networks (IJCNN), 2014
Domain transfer learning aims to learn an effective classifier for a target domain, where only a few labeled samples are available, with the help of many labeled samples from a source domain. The source and target domain samples usually share the same features and class label space, but have significantly different In these experiments error of the ...
Jim Jing-Yan Wang, Yijun Sun, Halima Bensmail   +2 more
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Nuclear Domains and the Nuclear Matrix

1996
This overview describes the spatial distribution of several enzymatic machineries and functions in the interphase nucleus. Three general observations can be made. First, many components of the different nuclear machineries are distributed in the nucleus in a characteristic way for each component.
R, van Driel, D G, Wansink, B, van Steensel, M A, Grande, W, Schul, L, de Jong   +5 more
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Preconditioning Capacitance Matrix Problems in Domain Imbedding

SIAM Journal on Scientific Computing, 1994
The finite element method with piecewise linear functions is considered for a second-order elliptic problem in a specific domain. The domain is the square with 1/8 part of it cut out by the straight line crossing the middles of two adjacent sides. The domain imbedding method reduces the problem to the solution of two subsidiary problems. One of them is
Proskurowski, Wlodek, Vassilevski, Panayot S.   +1 more
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Discriminative Kernel Matrix for Domain Adaptation

Electrical Engineering (ICEE), Iranian Conference on, 2018
In this paper, we investigate the unsupervised domain transfer learning in which there is no label in the target samples while the source samples are all labeled. In our approach the target and source samples are transferred to a new domain and each target sample is constructed by from the linear combination of the source samples in the new transformed
Parisa Razzaghi, Parvin Razzaghi
openaire   +1 more source