In the machine learning community it is generally believed that graph Laplacians corresponding to a finite sample of data points converge to a continuous Laplace operator if the s...
Matthias Hein, Jean-Yves Audibert, Ulrike von Luxb...
This paper presents postponed updates, a new strategy for TD methods that can improve sample efficiency without incurring the computational and space requirements of model-based ...
Sub-Nyquist sampling techniques for Wireless Sensor Networks (WSN) are gaining increasing attention as an alternative method to capture natural events with desired quality while mi...
The aim of the given paper is development of a recursive approach for calculating the statistics of decimated realizations of a basic discrete-time signal, obtained by sampling a c...
Abstract— We present a proof for the probabilistic completeness of RRT-based algorithms when planning with constraints on end-effector pose. Pose constraints can induce lowerdime...