When selecting alternatives from large amounts of data, trade-offs play a vital role in everyday decision making. In databases this is primarily reflected by the top-k retrieval p...
This paper presents a novel evolutionary approach of approximating the shape of the Pareto-optimal set of multi-objective optimization problems. The evolutionary algorithm (EA) use...
In this paper, we propose a multilevel cooperative coevolution (MLCC) framework for large scale optimization problems. The motivation is to improve our previous work on grouping ba...
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
We introduce a method to discover optimal local patterns, which concisely describe the main trends in a time series. Our approach examines the time series at multiple time scales ...