We present techniques for discovering and exploiting regularity in large curvilinear data sets. The data can be based on a single mesh or a mesh composed of multiple submeshes (al...
We consider wireless multihop data networks with random multi-access mechanisms at the MAC layer. In general, our aim is to study the performance as perceived by users in a dynamic...
We present a closed set data mining paradigm which is particularly e ective for uncovering the kind of deterministic, causal dependencies that characterize much of basic science. ...
Abstract—A multicast flow control framework for data traffic traversing both a wired and wireless network is proposed. Markov-modulated fluid (MMF) models are used for the rec...
We start by showing that in an active learning setting, the Perceptron algorithm needs Ω( 1 ε2 ) labels to learn linear separators within generalization error ε. We then prese...
Sanjoy Dasgupta, Adam Tauman Kalai, Claire Montele...