activity
20192024
most citedMelody: Generating and Visualizing Machine Learning Model Summary to Understand Data and Classifiers Together

12 citations · 18 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG20224 cited

TensorAnalyzer: Identification of Urban Patterns in Big Cities using Non-Negative Tensor Factorization

Jaqueline Silveira, Germain García, Afonso Paiva +3

Extracting relevant urban patterns from multiple data sources can be difficult using classical clustering algorithms since we have to make a suitable setup of the hyperparameters o…

cs.LG20222 cited

Topological Representations of Local Explanations

Peter Xenopoulos, Gromit Chan, Harish Doraiswamy +3

Local explainability methods -- those which seek to generate an explanation for each prediction -- are becoming increasingly prevalent due to the need for practitioners to rational…

stat.AP2020

CrimAnalyzer: Understanding Crime Patterns in São Paulo City

Garcia-Zanabria, Germain, Silveira +13

São Paulo is the largest city in South America, with high criminality rates. The number and type of crimes varies considerably around the city, assuming different patterns dependin…

cs.GR2020

TopoMap: A 0-dimensional Homology Preserving Projection of High-Dimensional Data

Harish Doraiswamy, Julien Tierny, Paulo J. S. Silva +2

Multidimensional Projection is a fundamental tool for high-dimensional data analytics and visualization. With very few exceptions, projection techniques are designed to map data fr…

cs.HC202012 cited

Melody: Generating and Visualizing Machine Learning Model Summary to Understand Data and Classifiers Together

Gromit Yeuk-Yin Chan, Enrico Bertini, Luis Gustavo Nonato +2

With the increasing sophistication of machine learning models, there are growing trends of developing model explanation techniques that focus on only one instance (local explanatio…

cs.GR2019

GLoG: Laplacian of Gaussian for Spatial Pattern Detection in Spatio-Temporal Data

Luis Gustavo Nonato, Fabiano Petronetto e Claudio Silva

Boundary detection has long been a fundamental tool for image processing and computer vision, supporting the analysis of static and time-varying data. In this work, we built upon t…