18 citations · 33 across the 5 of their papers we have counts for
5 papers
Semi-supervised Learning on Large Graphs: is Poisson Learning a Game-Changer?
Canh Hao Nguyen
We explain Poisson learning on graph-based semi-supervised learning to see if it could avoid the problem of global information loss problem as Laplace-based learning methods on lar…
Central-Smoothing Hypergraph Neural Networks for Predicting Drug-Drug Interactions
Duc Anh Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
Predicting drug-drug interactions (DDI) is the problem of predicting side effects (unwanted outcomes) of a pair of drugs using drug information and known side effects of many pairs…
Learning subtree pattern importance for Weisfeiler-Lehmanbased graph kernels
Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
Graph is an usual representation of relational data, which are ubiquitous in manydomains such as molecules, biological and social networks. A popular approach to learningwith graph…
On Convex Clustering Solutions
Canh Hao Nguyen, Hiroshi Mamitsuka
Convex clustering is an attractive clustering algorithm with favorable properties such as efficiency and optimality owing to its convex formulation. It is thought to generalize bot…
Learning on Hypergraphs with Sparsity
Canh Hao Nguyen, Hiroshi Mamitsuka
Hypergraph is a general way of representing high-order relations on a set of objects. It is a generalization of graph, in which only pairwise relations can be represented. It finds…