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As the projection of the real world, videos usually have many repeated patterns with similar structures cross regions, presenting strong non-local correlations. Moreover, different videos own different characteristics. Exploitation of the non-local correlations by off-line training of transforms has attracted considerable attention over the past years for compression. However, the samples used for...
Optimization problems with more than three objectives, i.e., many-objective problems (MaOPs), have gained more and more attentions in the field of evolutionary multi-objective optimization (EMO) in that the powerful Pareto comparisons and evolutionary strategies are very scarce. Particle swarm optimization (PSO) is an effective method for multi-objective problems, however, it has not been well scaled...
Surrogate-assisted interactive genetic algorithms (IGAs) are found to be very effective in reducing human fatigue. Different from models used in most surrogate-assisted evolutionary algorithms, surrogates in IGA must be able to handle the inherent uncertainties in fitness assignment by human users, where, e.g., interval-based fitness values are assigned to individuals. This poses another challenge...
Interactive genetic algorithms (IGAs) are effective methods of tackling optimization problems involving qualitative indices by incorporating a user's evaluations into traditional genetic algorithms. The problem of user fatigue resulting from the user's evaluations, however, has a negative influence on the performance of these algorithms. Substituting the user's evaluations with various surrogate models...
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