Has experience in Computer Science, focusing on Methodology and Computational Techniques (Source: Lattes Curriculum)
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Finding the K Nearest Neighbors Graph (kNNG) of a dataset is an essential estimation used in several algorithms, such as clustering and anomaly detection. However, this operation is costly since when calculating all k neighbors of all points in the set, there is a quadratic complexity concerning the size of the data set. Thus, there is a physical limitation in the execution of these algor…
Clustering is an unsupervised machine-learning task essential to several applications. In this way, some algorithms need the k Nearest Neighbors Graph (k NNG) as part of clustering. However, finding the k NNG may be a computationally costly operation since calculating all k neighbors of all points in the set is needed, resulting in a quadratic complexity concerning the size of a data set.…
| 1 / 1 | Completed scholarships in Brazil |
| 1 / 1 | Completed scholarships abroad |
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