We investigate the notions of may- and mustapproximation in Erratic Idealized Algol (a nondeterministic extension of Idealized Algol), and give explicit characterizations of both ...
Abstract. We consider a Stackelberg pricing problem in directed networks. Tariffs have to be defined by an operator, the leader, for a subset of the arcs, the tariff arcs. Clien...
Alexander Grigoriev, Stan P. M. van Hoesel, Anton ...
We explore the striking mathematical connections that exist between market scoring rules, cost function based prediction markets, and no-regret learning. We first show that any c...
Most of the work on the Vapnik-Chervonenkis dimension of neural networks has been focused on feedforward networks. However, recurrent networks are also widely used in learning app...
We address the problem of auditing an election when precincts may have different sizes. Prior work in this field has emphasized the simpler case when all precincts have the same s...