This paper studies learning node representations with GNNs for unsupervi...
In this paper, we study the statistical properties of the kernel k-means...
Theoretical analysis of the divide-and-conquer based distributed learnin...
Theoretical analysis of the divide-and-conquer based distributed learnin...
In this paper, after observing that different training data instances af...
Due to the high cost of manual annotation, learning directly from the we...
Deep learning, which is especially formidable in handling big data, has
...
Manifold regularization, such as laplacian regularized least squares (La...
While deep learning models and techniques have achieved great empirical
...
A plain well-trained deep learning model often does not have the ability...