Return random walks for link prediction
M Curado - Information Sciences, 2020 - Elsevier
In this paper we propose a new method, Return Random Walk, for link prediction to infer
new intra-class edges while minimizing the amount of inter-class noise, and we show how to …
new intra-class edges while minimizing the amount of inter-class noise, and we show how to …
Artificial intelligence in colorectal cancer diagnosis using clinical data: non-invasive approach
Colorectal cancer is the third most common and second most lethal tumor globally, causing
900,000 deaths annually. In this research, a computer aided diagnosis system was …
900,000 deaths annually. In this research, a computer aided diagnosis system was …
Early detection of Alzheimer's disease: Detecting asymmetries with a return random walk link predictor
Alzheimer's disease has been extensively studied using undirected graphs to represent the
correlations of BOLD signals in different anatomical regions through functional magnetic …
correlations of BOLD signals in different anatomical regions through functional magnetic …
[HTML][HTML] Network embedding from the line graph: Random walkers and boosted classification
In this paper, we propose to embed edges instead of nodes using state-of-the-art
neural/factorization methods (DeepWalk, node2vec, NetMF). These methods produce latent …
neural/factorization methods (DeepWalk, node2vec, NetMF). These methods produce latent …
Dirichlet densifier bounds: Densifying beyond the spectral gap constraint
In this paper, we characterize the universal bounds of our recently reported Dirichlet
Densifier. In particular we aim to study the impact of densification on the bounding of intra …
Densifier. In particular we aim to study the impact of densification on the bounding of intra …