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20192021
most citedSemi-Automatic Data Annotation guided by Feature Space Projection

40 citations · 42 across the 5 of their papers we have counts for

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cs.LG2021

Iterative Pseudo-Labeling with Deep Feature Annotation and Confidence-Based Sampling

Barbara C Benato, Alexandru C Telea, Alexandre X Falcão

Training deep neural networks is challenging when large and annotated datasets are unavailable. Extensive manual annotation of data samples is time-consuming, expensive, and error-…

cs.LG20211 cited

HyperNP: Interactive Visual Exploration of Multidimensional Projection Hyperparameters

Gabriel Appleby, Mateus Espadoto, Rui Chen +4

Projection algorithms such as t-SNE or UMAP are useful for the visualization of high dimensional data, but depend on hyperparameters which must be tuned carefully. Unfortunately, i…

cs.LG202040 cited

Semi-Automatic Data Annotation guided by Feature Space Projection

Barbara Caroline Benato, Jancarlo Ferreira Gomes, Alexandru Cristian Telea +1

Data annotation using visual inspection (supervision) of each training sample can be laborious. Interactive solutions alleviate this by helping experts propagate labels from a few…

cs.LG20201 cited

Supporting Optimal Phase Space Reconstructions Using Neural Network Architecture for Time Series Modeling

Lucas Pagliosa, Alexandru Telea, Rodrigo Mello

The reconstruction of phase spaces is an essential step to analyze time series according to Dynamical System concepts. A regression performed on such spaces unveils the relationshi…

cs.LG2019

Deep Learning Multidimensional Projections

Mateus Espadoto, Nina S. T. Hirata, Alexandru C. Telea

Dimensionality reduction methods, also known as projections, are frequently used for exploring multidimensional data in machine learning, data science, and information visualizatio…