We consider the problem of optimality, in a minimax sense, and adaptivity to the margin and to regularity in binary classification. We prove an oracle inequality, under the margin ...
When we model a phenomenon we apply a perspective on the phenomenon. The perspective decides which properties we include in the model. It also decides how we conceive a phenomenon ...
We propose a model-based learning algorithm, the Adaptive Aggregation Algorithm (AAA), that aims to solve the online, continuous state space reinforcement learning problem in a de...
We propose and investigate the notion of aggregate message authentication codes (MACs) which have the property that multiple MAC tags, computed by (possibly) different senders on ...
We consider problems where several individuals each need to make a yes/no choice regarding a number of issues and these choices then need to be aggregated into a collective choice...