In this report, we consider the problem of real-time transmission scheduling over time-varying channels. We first formulate the transmission scheduling problem as a Markov decisio...
Abstract—This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discu...
We recall the basic idea of an algebraic approach to learning Bayesian network (BN) structures, namely to represent every BN structure by a certain (uniquely determined) vector, c...
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...
—In-field diagnosability of electronic components in larger systems such as automobiles becomes a necessity for both customers and system integrators. Traditionally, functional ...