We study learning scenarios in which multiple learners are involved and “nature” imposes some constraints that force the predictions of these learners to behave coherently. Thi...
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
We demonstrate a framework for improving the availability of cluster based Internet services. Our approach models Internet services as a collection of interconnected components, e...
While there is a large class
of Multiple-Target Tracking (MTT) problems for which batch
processing is possible and desirable, batch MTT remains relatively
unexplored in comparis...
—We present a new technique for statistical static timing analysis (SSTA) based on Markov chain Monte Carlo (MCMC), that allows fast and accurate estimation of the right-hand tai...
Yashodhan Kanoria, Subhasish Mitra, Andrea Montana...