Viability Principles for Constrained Optimization Using a (1+1)-CMA-ES

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Machine intelligence greatly impacts almost all domains of our societies. It is profoundly changing the field of mechanical engineering with new technical possibilities and processes. The education of future engineers also needs to adapt in terms of techni ...

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Pareto-like sequential sampling heuristic for global optimisation

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In this paper, we propose a simple global optimisation algorithm inspired by Pareto’s principle. This algorithm samples most of its solutions within prominent search domains and is equipped with a self-adaptive mechanism to control the dynamic tightening o ...

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An efficient quantum algorithm for the time evolution of parameterized circuits

Giuseppe Carleo, Filippo Vicentini, Stefano Barison

We introduce a novel hybrid algorithm to simulate the real-time evolution of quantum systems using parameterized quantum circuits. The method, named "projected - Variational Quantum Dynamics" (p-VQD) realizes an iterative, global projection of the exact ti ...

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Spatial areas of genotype probability: Predicting the spatial distribution of adaptive genetic variants under future climatic conditions

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In a context of rapid global change, one of the key components for the survival of species is their genetic evolutionary potential for adaptation. Many methods have been developed to identify genetic variants underpinning adaptation to climate, but few too ...

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Roundtable Panel Discussion at DAC 2019: Evolutionary Computing or Heuristic Forever?

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As demands for computing have been continuously increasing, various solutions have been proposed. Some approaches deal with improving algorithms and software programs, mainly through the tuning of advanced heuristics and learning methods. Some other tackle ...

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The electric autonomous dial-a-ride problem

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This thesis develops mathematical programming frameworks to operate electric autonomous vehicles in the context of ride-sharing services. The introduced problem is a novel variant of the Dial-a-Ride Problem (DARP), denoted by the electric Autonomous Dial-a ...

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Pipeline Synthesis and Optimization from Branched Feedback Dataflow Programs

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The population genetics of crypsis in vertebrates: recent insights from mice, hares, and lizards

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By combining well-established population genetic theory with high-throughput sequencing data from natural populations, major strides have recently been made in understanding how, why, and when vertebrate populations evolve crypsis. Here, we focus on backgr ...

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Global Convergence and Variance Reduction for a Class of Nonconvex-Nonconcave Minimax Problems

Negar Kiyavash

Nonconvex minimax problems appear frequently in emerging machine learning applications, such as generative adversarial networks and adversarial learning. Simple algorithms such as the gradient descent ascent (GDA) are the common practice for solving these ...

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Genomic Analysis of European Drosophila melanogaster Populations Reveals Longitudinal Structure, Continent-Wide Selection, and Previously Unknown DNA Viruses

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Genetic variation is the fuel of evolution, with standing genetic variation especially important for short-term evolution and local adaptation. To date, studies of spatiotemporal patterns of genetic variation in natural populations have been challenging, a ...

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Spatial areas of genotype probability: Predicting the spatial distribution of adaptive genetic variants under future climatic conditions

Stéphane Joost, Oliver Michele Selmoni, Estelle Rochat

2021

Genomic Analysis of European Drosophila melanogaster Populations Reveals Longitudinal Structure, Continent-Wide Selection, and Previously Unknown DNA Viruses

Bart Deplancke

2020