This paper deals with the problem of constructing a Hamiltonian cycle of optimal weight, called TSP. We show that TSP is 2/3-differential approximable and can not be differential a...
We consider the existence of a linear weak learner for boosting algorithms. A weak learner for binary classification problems is required to achieve a weighted empirical error on t...
In this paper, we present a framework for a robotic system with the ability to perform real-world manipulation tasks. The complexity of such tasks determines the precision and fre...
Danica Kragic, Lars Petersson, Henrik I. Christens...
Abstract--Additive noise removal from a given signal is an important problem in signal processing. Among the most appealing aspects of this field are the ability to refer it to a w...
We prove new lower bounds for learning intersections of halfspaces, one of the most important concept classes in computational learning theory. Our main result is that any statist...