Search Results - "Costa, Anderson F B F"

Clustering interval data through kernel-induced feature space by da Costa, Anderson F. B. F., Pimentel, Bruno A., de Souza, Renata M. C. R.

“…Recently, kernel-based clustering in feature space has shown to perform better than conventional clustering methods in unsupervised classification. In this…”
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IP traffic classifiers applied to DiffServ networks by Taynnan Barros, Michael, Gomes, Reinaldo, Sampaio de Alencar, Marcelo, da Costa, Anderson F. B. F.

“…The future Internet scenario consists of a higher number of users and applications, which demand more resources from the communication infrastructure…”
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Enabling high-level network programming: A northbound API for Software-Defined Networks by Rocha Vasconcelos, Cesar, Gomes, Reinaldo Cezar M., Costa, Anderson F. B. F., Dias C. da Silva, Daniella

“…Software-Defined Networking (SDN) is a new paradigm that is attracting significant attention from both academy and industry. In recent years, increasing…”
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Input space versus feature space in kernel-based interval fuzzy C-Means clustering by Pimentel, Bruno A., da Costa, Anderson F. B. F., de Souza, Renata M. C. R.

“…The main property of kernel methods is that they can implicitly perform a nonlinear mapping of the input data into a high-dimensional space. This mapping…”
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Kernel-based fuzzy clustering of interval data by Pimentel, Bruno A., da Costa, Anderson F. B. F., de Souza, Renata M. C. R.

“…Kernel clustering methods have been very important in application of non-supervised machine learning to real problems. Kernel methods possess many advantages…”
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A kernel k-means clustering method for symbolic interval data by Costa, Anderson F B F, Pimentel, Bruno A, de Souza, Renata M C R

“…Kernel k-means algorithms have recently been shown to perform better than conventional k-means algorithms in unsupervised classification. In this paper we…”
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