Online Gaussian Process
Online Gaussian Process (OGP) extends the Bayesian nonparametric GP framework to streaming or sequentially arriving data. Instead of recomputing the full GP posterior from scratch as each observation arrives, OGP maintains a compact summary — a sparse set of inducing points — and updates it incrementally, making probabilistic regression and classification feasible in real-time and large-scale settings.
Rekodi ya chanzo
Nukuu zimehamishwa kwa uhalisi kutoka kwa rekodi ya chanzo cha mbinu. Hakuna uthibitisho wa kiwango cha dai unaodokezwa kutoka kwao.
- Csató, L. & Opper, M. (2002). Sparse on-line Gaussian processes. Neural Computation, 14(3), 641–668. · DOI 10.1162/089976602317250933
- Engel, Y., Mannor, S. & Meir, R. (2004). The kernel recursive least-squares algorithm. IEEE Transactions on Signal Processing, 52(8), 2275–2285. · DOI 10.1109/TSP.2004.830985
Madai yaliyotunzwa
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Mbinu zinazohusiana
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