We consider the problem of learning a Riemannian metric associated with a given differentiable manifold and a set of points. Our approach to the problem involves choosing a metric...
An Estimation of Distribution Algorithm (EDA) is proposed to approach the Hybrid Flow Shop with Sequence Dependent Setup Times and Uniform Machines in parallel (HFSSDST-UM) proble...
It is well known that many hard tasks considered in machine learning and data mining can be solved in a rather simple and robust way with an instanceand distance-based approach. In...
— We revisit the problem of synthesis of service composition in the context of service oriented architecture from a tree automata perspective. Comparing to existing finite state...
Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...