Solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. Evolutionary algorithms (EAs) were initially extended and applied ...
We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to combinatorial optimization problems over a...
Most previous research into the job-shop scheduling problem has concentrated on finding a single optimal solution (e.g., makespan), even though the actual requirement of most prod...
Deformable template models, in which a shape model and its corresponding appearance model are deformed to optimally fit an object in the image, have proven successful in many medic...
This paper discusses decision making in the practically important situation where only partial prior information on the stochastic behavior of the states of nature expressed by im...