Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
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...
Multi-user virtual environments (MUVEs) seem to have great potential in education. Current educational uses of MUVEs seem to exploit them more as group interaction platforms and le...
Ioannis Vrellis, Nikiforos M. Papachristos, Joan B...
We study the problem of learning large margin halfspaces in various settings using coresets to show that coresets are a widely applicable tool for large margin learning. A large m...