Empirical risk minimization offers well-known learning guarantees when training and test data come from the same domain. In the real world, though, we often wish to adapt a classi...
John Blitzer, Koby Crammer, Alex Kulesza, Fernando...
We analyze the convergence of randomized trace estimators. Starting at 1989, several algorithms have been proposed for estimating the trace of a matrix by 1 M M i=1 zT i Azi, where...
A low complexity user scheduling algorithm based on a novel adaptive Markov chain Monte Carlo (AMCMC) method is proposed to achieve the maximal sum capacity in an uplink multiple-i...
Yangyang Zhang, Chunlin Ji, Yi Liu, Wasim Q. Malik...
In this paper, we first propose a new continuous action-set learning automaton and theoretically study its convergence properties and show that it converges to the optimal action....
Abstract. We study Facility Location games played by n agents situated on the nodes of a graph. Each agent orders installation of a facility at a node of the graph and pays connect...