Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Greedy search is commonly used in an attempt to generate solutions quickly at the expense of completeness and optimality. In this work, we consider learning sets of weighted actio...
For systems where exact constitutive relations are unknown, a microscopic level description can be alternatively used. As microscopic simulations are computationally expensive, th...
The responsiveness of networked applications is limited by communications delays, making network distance an important parameter in optimizing the choice of communications peers. S...
Local search (LS) algorithms are among the most powerful techniques for solving computationally hard problems in combinatorial optimization. These algorithms could be viewed as &q...