This paper, motivated by functional brain imaging applications, is interested in the discovery of stable spatio-temporal patterns. This problem is formalized as a multi-objective multi-modal optimization problem: on one hand, the target patterns must show a good stability in a wide spatio-temporal region (antagonistic objectives); on the other hand, experts are interested in finding all such pa...

Gait optimization is a basic yet challenging problem for both quadrupedal and bipedal robots. Although techniques for automating the process exist, most involve local function optimization procedures that suffer from three key drawbacks. Local optimization techniques are naturally plagued by local optima, make no use of the expensive gait evaluations once a local step is taken, and do not expli...

In order to solve multiple constraints in the existing polygonal approximation algorithms of digital curves, a new algorithm is proposed in this article. Each control constraint is taken as the optimization objective respectively and the idea of multi-objective optimization is also applied. Vertex positions of the intermediate approximation polygon are represented by a binary sequence, and Hamm...

Machine learning models are often tuned by nesting optimization of model weights inside the optimization of hyperparameters. We give a method to collapse this nested optimization into joint stochastic optimization of weights and hyperparameters. Our process trains a neural network to output approximately optimal weights as a function of hyperparameters. We show that our technique converges to l...

This paper presents a lens system design algorithm using the covariance matrix adaptation evolution strategy (CMA-ES), which is one of the most powerful self-adaptation mechanisms. The lens design problem is a very difficult optimization problem because the typical search space is a complicated multidimensional space including many local optima, non-linearities, and strongly correlated paramete...

Rechargeable Zn–air batteries (ZABs) can play a significant role in the transition to cleaner and more sustainable energy system due their high theoretical density, cell voltage, environmental friendliness. ZAB’s air cathode is principal determinant predicting battery’s overall performance, as it responsible for catalyzing oxygen reduction reaction (ORR) evolution (OER) during discharging charg...

This paper provides empirical evidence in support of the hypothesis, that a populational extension of simulated annealing with cooperative transitions leads to a significant increase of efficiency and solution quality for a given combinatorial optimization problem (and a neighborhood relation) if and only if the globally optimal solution is located "close" to the center of all locally optimal s...

It is well known that multi-surface segmentation can be cast as a multi-labeling problem. Different segments may belong to the same semantic object which may impose various inter-segment constraints [1]. In medical applications, there are a lot of scenarios where upper bounds on the Hausdorff distances between subsequent surfaces are known. We show that incorporating these priors into multi-sur...

The p-principal points of a random variable X with finite second moment are those p points in R minimizing the expected squared distance from X to the closest point. Although the determination of principal points involves in general the resolution of a multiextremal optimization problem, existing procedures in the literature provide just a local optimum. In this paper we show that standard Glob...

This paper presents a novel differential evolution algorithm for protein folding optimization that is applied to a three-dimensional AB off-lattice model. The proposed algorithm includes two new mechanisms. A local search is used to improve convergence speed and to reduce the runtime complexity of the energy calculation. For this purpose, a local movement is introduced within the local search. ...