We study the stochastic machine replenishment problem, which is a canonical special case of closed multiclass queuing systems in Markov decision theory. The problem models the sche...
This paper derives Monte Carlo simulation estimators to compute option price derivatives, i.e., the `Greeks,' under Heston's stochastic volatility model and some variant...
Stochastic Petri nets (SPNs) have proven to be a powerful and enduring graphically-oriented framework for modelling and performance analysis of complex systems. This tutorial focu...
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
This study addresses the problem of unsupervised visual learning. It examines existing popular model order selection criteria before proposes two novel criteria for improving visu...