We consider the problem of learning a coefficient vector x0 ∈ RN from noisy linear observation y = Ax0 + w ∈ Rn . In many contexts (ranging from model selection to image proce...
— This paper presents work on sensor-based motion planning in initially unknown dynamic environments. Motion detection and modeling are combined with a smooth navigation function...
Abstract. This paper studies a risk minimization approach to estimate a transformation model from noisy observations. It is argued that transformation models are a natural candidat...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
In this paper, we show that the standard point of view of the neuroimaging community about fMRI time series alignment should be revisited to overcome the bias induced by activation...
— Assume the reliability of a connection is determined by the number of distinct risks associated with the path. We study the most reliable routing for WDM networks with arbitrar...