Various multi–objective evolutionary algorithms (MOEAs) have obtained promising results on various numerical multi– objective optimization problems. The combination with gradi...
In this paper we introduce Structured Local Predictors (SLP) – A new formulation that considers the image labelling problem from a structured learning point of view. SLP are loc...
We introduce Hegel and Fichte’s dialectic as a search meta-heuristic for constraint satisfaction and optimization. Dialectic is an appealing mental concept for local search as it...
Multiple kernel learning (MKL) uses a weighted combination of kernels where the weight of each kernel is optimized during training. However, MKL assigns the same weight to a kerne...
In the paper, we investigate the use of reinforcement learning in CBR for estimating and managing a legacy case base for playing the game of Tetris. Each case corresponds to a loc...