In reinforcement learning, an agent tries to learn a policy, i.e., how to select an action in a given state of the environment, so that it maximizes the total amount of reward it ...
By mapping a set of input images to points in a lowdimensional manifold or subspace, it is possible to efficiently account for a small number of degrees of freedom. For example, i...
Support vector machines (SVMs) have been widely used in multimedia retrieval to learn a concept in order to find the best matches. In such a SVM active learning environment, the ...
Over the last decade, programmable Network Processors (NPs) have become widely used in Internet routers and other network components. NPs enable rapid development of complex packe...
Charlie Wiseman, Jonathan S. Turner, Michela Becch...