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Found 6 papers, 1 papers with code
Framework for Designing Filters of Spectral Graph Convolutional Neural Networks in the Context of Regularization Theory
In this work, we explore the regularization properties of graph Laplacian and proposed a generalized framework for regularized filter designs in spectral GCNNs.
Neighborhood Preserving Kernels for Attributed Graphs
We describe the design of a reproducing kernel suitable for attributed graphs, in which the similarity between the two graphs is defined based on the neighborhood information of the graph nodes with the aid of a product graph formulation.
An efficient scheme based on graph centrality to select nodes for training for effective learning
The process of selecting points for training a machine learning model is often a challenging task.
A Comparative study of Hyper-Parameter Optimization Tools
For a robust performance of a model, it is necessary to find out the right hyper-parameter combination.
An Ensemble Model for Face Liveness Detection
In this paper, we present a passive method to detect face presentation attack a. k. a face liveness detection using an ensemble deep learning technique.
A PSO Based Method to Generate Actionable Counterfactuals for High Dimensional Data
We propose a simple objective function for the optimization of the instance-centric CF generation problem.
