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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_1724525835444, 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 -