16 citations · 54 across the 10 of their papers we have counts for
4 papers · 1 filter
Hierarchy exploitation to detect missing annotations on hierarchical multi-label classification
Miguel Romero, Felipe Kenji Nakano, Jorge Finke +2
The availability of genomic data has grown exponentially in the last decade, mainly due to the development of new sequencing technologies. Based on the interactions between genes (…
Feature extraction using Spectral Clustering for Gene Function Prediction using Hierarchical Multi-label Classification
Miguel Romero, Oscar Ramírez, Jorge Finke +1
Gene annotation addresses the problem of predicting unknown associations between gene and functions (e.g., biological processes) of a specific organism. Despite recent advances, th…
A Top-down Supervised Learning Approach to Hierarchical Multi-label Classification in Networks
Miguel Romero, Jorge Finke, Camilo Rocha
Node classification is the task of inferring or predicting missing node attributes from information available for other nodes in a network. This paper presents a general prediction…
Spectral Evolution with Approximated Eigenvalue Trajectories for Link Prediction
Miguel Romero, Jorge Finke, Camilo Rocha +1
The spectral evolution model aims to characterize the growth of large networks (i.e., how they evolve as new edges are established) in terms of the eigenvalue decomposition of the…