D
Diego Furtado Silva
Researcher at Federal University of São Carlos
Publications - 69
Citations - 2051
Diego Furtado Silva is an academic researcher from Federal University of São Carlos. The author has contributed to research in topics: Dynamic time warping & Feature extraction. The author has an hindex of 20, co-authored 65 publications receiving 1533 citations. Previous affiliations of Diego Furtado Silva include University of São Paulo & Spanish National Research Council.
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Proceedings ArticleDOI
Matrix Profile I: All Pairs Similarity Joins for Time Series: A Unifying View That Includes Motifs, Discords and Shapelets
Chin-Chia Michael Yeh,Yan Zhu,Liudmila Ulanova,Nurjahan Begum,Yifei Ding,Hoang Anh Dau,Diego Furtado Silva,Abdullah Mueen,Eamonn Keogh +8 more
TL;DR: A novel scalable algorithm for time series subsequence all-pairs-similarity-search that computes the answer to the time series motif and time series discord problem as a side-effect, and incidentally provides the fastest known algorithm for both these extensively-studied problems.
Journal ArticleDOI
Class imbalance revisited: a new experimental setup to assess the performance of treatment methods
TL;DR: A simple experimental design to assess the performance of class imbalance treatment methods and a statistical procedure aimed to evaluate the relative degradation and recoveries, based on confidence intervals are proposed.
Proceedings ArticleDOI
Speeding up all-pairwise dynamic time warping matrix calculation
TL;DR: This paper proposes the first exact approach for speeding up the all-pairwise DTW matrix calculation and demonstrates that the algorithm reduces the runtime in approximately 50% on average and up to one order of magnitude in some datasets.
Journal ArticleDOI
Time series joins, motifs, discords and shapelets: a unifying view that exploits the matrix profile
Chin-Chia Michael Yeh,Yan Zhu,Liudmila Ulanova,Nurjahan Begum,Yifei Ding,Hoang Anh Dau,Zachary Zimmerman,Diego Furtado Silva,Abdullah Mueen,Eamonn Keogh +9 more
TL;DR: A novel scalable algorithm for time series subsequence all-pairs-similarity-search that computes the answer to the time series motif and time series discord problem as a side-effect and incidentally provides the fastest known algorithm for both these extensively-studied problems.
Proceedings ArticleDOI
Data stream classification guided by clustering on nonstationary environments and extreme verification latency
TL;DR: Sao Paulo Research Foundation (FAPESP) (grant numbers 2011/17698-5, 2012/50714-7, 2013/26151-5)