Accurate On-line Support Vector Regression

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On-line regression algorithms for learning mechanical models of robots: A survey (2011, methodology): “The focus of this survey being incremental and local approaches, we must mention that an svm approach endowed with these properties and called l o svr is presented in Choi et al. [24]. l o svr is built on a previous incremental svm algorithm presented in Ma et al. [61].”
Incremental learning for ν-Support Vector Regression (2015, positive): “Martin (2002) and Ma, Theiler, and Perkins (2003) introduced it to ϵ -SVR (Vapnik, 1998) and developed an accurate on-line support vector regression (AOSVR).”
Model learning for robot control: a survey (2011, background): “Incremental support vector machine (Ma et al. 2005) Global Incremental Yes Oðn(2)Þ Inverse dynamics (Choi et al.”
Traditional and recent approaches in background modeling for foreground detection: An overview (2014, methodology): “The background initialization is made using a batch algorithm and the background maintenance is achieved with an on-line SVR algorithm [175].”
Support Vector Regression (2007, methodology): “Following an incremental support vector classification algorithm [24], an accurate on-line support vector regression (AOSVR) has been developed.”