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Ferreira, J., de Matos, D. & Ribeiro, R. (2016). Fast and Extensible Online Multivariate Kernel Density Estimation. arXiv.

J. Ferreira et al.,  "Fast and Extensible Online Multivariate Kernel Density Estimation", in arXiv, 2016

@misc{ferreira2016_1732205281740,
	author = "Ferreira, J. and de Matos, D. and Ribeiro, R.",
	title = "Fast and Extensible Online Multivariate Kernel Density Estimation",
	year = "2016",
	howpublished = "Digital",
	url = "https://arxiv.org/abs/1606.02608"
}

TY  - GEN
TI  - Fast and Extensible Online Multivariate Kernel Density Estimation
T2  - arXiv
AU  - Ferreira, J.
AU  - de Matos, D.
AU  - Ribeiro, R.
PY  - 2016
UR  - https://arxiv.org/abs/1606.02608
AB  - We present xokde++, a state-of-the-art online kernel density estimation approach that maintains Gaussian mixture models input data streams. The approach follows state-of-the-art work on online density estimation, but was redesigned with computational efficiency, numerical robustness, and extensibility in mind. Our approach produces comparable or better results than the current state-of-the-art, while achieving significant computational performance gains and improved numerical stability. The use of diagonal covariance Gaussian kernels, which further improve performance and stability, at a small loss of modelling quality, is also explored. Our approach is up to 40 times faster, while requiring 90\% less memory than the closest state-of-the-art counterpart.
ER  -