Ensemble learning is a variational Bayesian method in which an intractable distribution is approximated by a lower-bound. Ensemble learning results in models with better generaliz...
—In the routing and cost sharing of multicast towards a group of potential receivers, cross-monotonicity is a property that states a user’s payment can only be smaller when ser...
Much real data consists of more than one dimension, such as financial transactions (eg, price × volume) and IP network flows (eg, duration × numBytes), and capture relationship...
Graham Cormode, Flip Korn, S. Muthukrishnan, Dives...
Solid frameworks and toolkits for design and analysis of embedded systems are of high importance, since they enable early reasoning about critical properties of a system. This pap...
Egor R. V. Bondarev, Michel R. V. Chaudron, Peter ...
Abstract— The impact of process variations increases as technology scales to nanometer region. Under large process variations, the path and arc/node criticality [18] provide effe...