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Semi-supervised Clustering Ensemble by Voting
clustering ensembles semi supervised clustering consensus function ensemble generation.
2012/9/18
Clustering ensemble is one of the most recent advances in unsupervised learning. It aims to combine the clustering results obtained using different algorithms or from different runs of ...
Bayesian semi-parametric forecasting with penalised splines and autoregressive errors
splines, autoregressive errors, semi-parametric regression, Bayesian
2012/9/18
Observational time series data often exhibit both cyclic temporal trends and autocorrelation and may also depend on covariates. As such, there is a need for exible regression models that are able to c...
Estimation of Scale and Hurst Parameters of Semi-Selfsimilar Processes
Hurst estimation Discrete self-similarity Fractional Brownian motion Semi-selfsimilar processes Scale parameter.
2012/9/19
The characteristic feature of semi-selfsimilar process is the invariance of its finite dimensional distributions by certain dilation for specific scaling factor. Estimating the scale parameter λand th...
Semi-parametric estimation of shifts
Semi-parametric estimation Empirical process Fourier transform
2009/9/16
We observe a large number of functions differing from each other only by a translation parameter. While the main pattern is unknown, we propose to estimate the shift parameters using M-estimators. Fou...