Current stochastic model checkers do not make counterexamples for property violations readily available. In this paper we apply directed explicit state space search to discrete- a...
The quality of multi-stage stochastic optimization models as they appear in asset liability management, energy planning, transportation, supply chain management, and other applicat...
Understanding how the structure of a network evolves over time is one of the most interesting and complex topics in the field of social networks. In our attempt to model the dynam...
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
The stochastic discrimination (SD) theory considers learning as building models of uniform coverage over data distributions. Despite successful trials of the derived SD method in s...