We develop a new method for proving explicit approximation lower bounds for TSP problems with bounded metrics improving on the best up to now known bounds. They almost match the b...
This paper examines the problem of learning with a finite and possibly large set of p base kernels. It presents a theoretical and empirical analysis of an approach addressing thi...
Abstract. In this paper we give a fully polynomial randomized approximation scheme (FPRAS) for the number of all matchings in hypergraphs belonging to a class of sparse, uniform hy...
Marek Karpinski, Andrzej Rucinski, Edyta Szymanska
We address the online linear optimization problem with bandit feedback. Our contribution is twofold. First, we provide an algorithm (based on exponential weights) with a regret of...
In many situations, Miniature Aerial Vehicles (MAVs) are limited to using only on-board sensors for navigation. This limits the data available to algorithms used for stabilization...