This paper describes a novel application of Statistical Learning Theory (SLT) for motion prediction. SLT provides analytical VC-generalization bounds for model selection; these bo...
Harry Wechsler, Zoran Duric, Fayin Li, Vladimir Ch...
In this paper we examine master regression algorithms that leverage base regressors by iteratively calling them on modified samples. The most successful leveraging algorithm for c...
In this paper we examine ensemble methods for regression that leverage or "boost" base regressors by iteratively calling them on modified samples. The most successful lev...
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
We study the problem of estimating the average of a Lipschitz continuous function f defined over a metric space, by querying f at only a single point. More specifically, we explore...