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We introduce the submodular Max-SAT problem. This problem is a natural generalization of the classical Max-SAT problem in which the additive objective function is replaced by a submodular one. We develop a randomized linear-time 2/3-approximation algorithm for the problem. Our algorithm is applicable even for the online variant of the problem. We also(More)
One of the most challenging recommendation tasks is recommending to a new, previously unseen user. This is known as the <i>user cold start</i> problem. Assuming certain features or attributes of users are known, one approach for handling new users is to initially model them based on their features. Motivated by an ad targeting application, this paper(More)
ROBOCAST is a multi-national project comprising several institutes which aim at outlining and implementing a prototype system for advanced, robot-assisted keyhole neurosurgery. This paper reports mainly on software and sensor aspects of the system in the pre- and intra-operative stage. We describe a comprehensive workflow of planning steps provided to the(More)
1 Regret Minimization In this lecture, our goal is to build a strategy with good performance when dealing with repeated games. Let us start with a simple model of regret. In this model a player performs a partial optimization on his actions. Following each action he updates his belief and selects the next actions, dependent on the outcome. We will also show(More)