Results 21 to 30 of about 5,249 (165)
Genome Medicine, 2019 Background Exome sequencing (ES) has been successfully applied in clinical detection of single nucleotide variants (SNVs) and small indels. However, identification of copy number variants (CNVs) using ES data remains challenging.
Avinash V. Dharmadhikari +34 more
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Angle-Based Parametrization with Evolutionary Optimization for OESCL-Band Y-Junction Splitters
Photonics, 2023 The design of passive photonic devices based on geometry optimization can lead to energy-efficient, small-footprint, and fabrication-ready geometries. In this work, we propose an angle-based parametrization method to optimize Y-junction splitters based ...
Roy Prosopio-Galarza +5 more
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Cirugía y Cirujanos, 2023 Antecedentes: La enfermedad venosa crónica es una patología frecuente y prevalente. Su tratamiento quirúrgico ha mostrado ser coste-efectivo. La endoablación térmica realizada como cirugía mayor ambulatoria (CMA) es la técnica de elección.
Renato Jiménez-Román +2 more
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Injecting CMA-ES into MOEA/D [PDF]
Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation, 2015 MOEA/D is an aggregation-based evolutionary algorithm which has been proved extremely efficient and effective for solving multiobjectiveoptimization problems. It is based on the idea of decomposing the original multi-objective problem into several singleobjective subproblems by means of well-defined scalarizing functions.
Zapotecas-Martínez, Saúl +5 more
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Anytime Bi-Objective Optimization with a Hybrid Multi-Objective CMA-ES (HMO-CMA-ES) [PDF]
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion, 2016 We propose a multi-objective optimization algorithm aimed at achieving good anytime performance over a wide range of problems. Performance is assessed in terms of the hypervolume metric. The algorithm called HMO-CMA-ES represents a hybrid of several old and new variants of CMA-ES, complemented by BOBYQA as a warm start.
Ilya Loshchilov, Tobias Glasmachers
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A global surrogate assisted CMA-ES [PDF]
Proceedings of the Genetic and Evolutionary Computation Conference, 2019 We explore the arguably simplest way to build an effective surrogate fitness model in continuous search spaces. The model complexity is linear or diagonal-quadratic or full quadratic, depending on the number of available data. The model parameters are computed from the Moore-Penrose pseudoinverse.
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On the Anytime Behavior of IPOP-CMA-ES [PDF]
, 2012 Anytime algorithms aim to produce a high-quality solution for any termination criterion. A recent proposal is to improve automatically the anytime behavior of single-objective optimization algorithms by incorporating the hypervolume, a well-known quality measure in multi-objective optimization, into an automatic configuration tool.
Manuel López-Ibáñez 0001 +2 more
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BCMA-ES: A Bayesian Approach to CMA-ES [PDF]
SSRN Electronic Journal, 2019 This paper introduces a novel theoretically sound approach for the celebrated CMA-ES algorithm. Assuming the parameters of the multi variate normal distribution for the minimum follow a conjugate prior distribution, we derive their optimal update at each iteration step. Not only provides this Bayesian framework a justification for the update of the CMA-
Eric Benhamou +3 more
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Enhancing Local Decisions in Agent-Based Cartesian Genetic Programming by CMA-ES
Systems, 2023 Cartesian genetic programming is a popular version of classical genetic programming, and it has now demonstrated a very good performance in solving various use cases. Originally, programs evolved by using a centralized optimization approach. Recently, an
Jörg Bremer, Sebastian Lehnhoff
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A (1+1)-CMA-ES for constrained optimisation [PDF]
Proceedings of the 14th annual conference on Genetic and evolutionary computation, 2012 This paper introduces a novel constraint handling approach for covariance matrix adaptation evolution strategies (CMA- ES). The key idea is to approximate the directions of the local normal vectors of the constraint boundaries by accumulating steps that violate the respective constraints, and to then reduce variances of the mutation distribution in ...
Dirk V. Arnold, Nikolaus Hansen
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