Coupling the periodic time-invariance of the wavelet transform with the view of thresholding as a projection yields a simple, recursive, wavelet-based technique for denoising sign...
Alyson K. Fletcher, Vivek K. Goyal, Kannan Ramchan...
Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
We present an algorithm for large-scale equality constrained optimization. The method is based on a characterization of inexact sequential quadratic programming (SQP) steps that ca...
The ability of an algorithm to accurately estimate the parameters of the geometric transformation which aligns two image profiles even in the presence of photometric distortions ...
An efficient and general multiple kernel learning (MKL) algorithm has been recently proposed by Sonnenburg et al. (2006). This approach has opened new perspectives since it makes ...