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Found 9 papers, 1 papers with code
Fairness in generative modeling
We design general-purpose algorithms for addressing fairness issues and mode collapse in generative modeling.
Improving Nevergrad's Algorithm Selection Wizard NGOpt through Automated Algorithm Configuration
Algorithm selection wizards are effective and versatile tools that automatically select an optimization algorithm given high-level information about the problem and available computational resources, such as number and type of decision variables, maximal number of evaluations, possibility to parallelize evaluations, etc.
EvolGAN: Evolutionary Generative Adversarial Networks
We propose to use a quality estimator and evolutionary methods to search the latent space of generative adversarial networks trained on small, difficult datasets, or both.
Versatile Black-Box Optimization
Choosing automatically the right algorithm using problem descriptors is a classical component of combinatorial optimization.
Polygames: Improved Zero Learning
Since DeepMind's AlphaZero, Zero learning quickly became the state-of-the-art method for many board games.
BCMA-ES: A Bayesian approach to CMA-ES
This paper introduces a novel theoretically sound approach for the celebrated CMA-ES algorithm.
Automatically Reinforcing a Game AI
In addition, we consider the case in which only one GPP is available - by decomposing this single GPP into several ones through the use of parameters or even simply random seeds.
Learning opening books in partially observable games: using random seeds in Phantom Go
Many artificial intelligences (AIs) are randomized.
A Critical Reassessment of Evolutionary Algorithms on the cryptanalysis of the simplified data encryption standard algorithm
In this paper we analyze the cryptanalysis of the simplified data encryption standard algorithm using meta-heuristics and in particular genetic algorithms.
