In recent years, deep learning has achieved remarkable achievements in many fields, including computer vision, natural language processing, speech re…

Jointly integrating aspect ratio and context has been extensively studied and shown performance improvement in traditional object detection systems s…

Many real-world applications reveal difficulties in learning classifiers from imbalanced data. The rising big data era has been witnessing more class…

The emerging concern about data privacy and security has motivated the proposal of federated learning, which allows nodes to only synchronize the loc…

The rapid evolving World Wide Web has produced a large amount of complex and heterogeneous network data. To facilitate network analysis algorithms, s…

Message-passing neural networks (MPNNs) have been successfully applied to representation learning on graphs in a variety of real-world applications. …

Most of the explanation methods for neural models are designed for general neural networks, while only few works exist for GNNs. In this paper, we presented a model-agnostic local interpretable explanation framework for GNN, which we call GraphLIME.…

Graph structured data has wide applicability in various domains such as physics, chemistry, biology, computer vision, and social networks, to name a …

Network structure optimization is a fundamental task in complex network analysis. However, almost all the research on Bayesian optimization is aimed …

Dispersion features of a graphene-coated semiconductor nanowire operating in the terahertz frequency band are consistently studied in the framework o…

In this paper, we apply the weak Galerkin method to solve the eigenvalue problems and the corresponding convergence analysis is also given. Furthermore, we also analyze the lower-bound property of the weak Galerkin method. Compared with the classica…

This article is devoted to computing the eigenvalue of the Laplace eigenvalue problem by the weak Galerkin (WG) finite element method with emphasis o…

A weak Galerkin (WG) finite element method for solving the stationary Stokes equations in two- or three- dimensional spaces by using discontinuous pi…

Low rank matrix approximation (LRMA) has drawn increasing attention in recent years, due to its wide range of applications in computer vision and mac…

We study the problem of attacking video recognition models in the black-box setting, where the model information is unknown and the adversary can onl…

Nodes performing different functions in a network have different roles, and these roles can be gleaned from the structure of the network. Learning la…

Recent advances show that two-dimensional linear discriminant analysis (2DLDA) is a successful matrix based dimensionality reduction method. However,…

Image deconvolution is still to be a challenging ill-posed problem for recovering a clear image from a given blurry image, when the point spread func…

In this section, we would like to report some numerical results for the weak Galerkin finite element method proposed and analyzed in previous sections. Here we use the following finite element space

A new weak Galerkin (WG) finite element method for solving the biharmonic equation in two or three dimensional spaces by using polynomials of reduced…

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