Search Results - "Jin, Yaochu"

Surrogate-assisted evolutionary computation: Recent advances and future challenges by Jin, Yaochu

“…Surrogate-assisted, or meta-model based evolutionary computation uses efficient computational models, often known as surrogates or meta-models, for…”
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A social learning particle swarm optimization algorithm for scalable optimization by Cheng, Ran, Jin, Yaochu

“…Social learning plays an important role in behavior learning among social animals. In contrast to individual (asocial) learning, social learning has the…”
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A Competitive Swarm Optimizer for Large Scale Optimization by Cheng, Ran, Jin, Yaochu

“…In this paper, a novel competitive swarm optimizer (CSO) for large scale optimization is proposed. The algorithm is fundamentally inspired by the particle…”
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A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization by Ran Cheng, Yaochu Jin, Olhofer, Markus, Sendhoff, Bernhard

“…In evolutionary multiobjective optimization, maintaining a good balance between convergence and diversity is particularly crucial to the performance of the…”
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RM-MEDA: A Regularity Model-Based Multiobjective Estimation of Distribution Algorithm by Qingfu Zhang, Qingfu Zhang, Aimin Zhou, Aimin Zhou, Yaochu Jin, Yaochu Jin

“…Under mild conditions, it can be induced from the Karush-Kuhn-Tucker condition that the Pareto set, in the decision space, of a continuous multiobjective…”
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Pareto-Based Multiobjective Machine Learning: An Overview and Case Studies by Yaochu Jin, Sendhoff, B.

“…Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple…”
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A Knee Point-Driven Evolutionary Algorithm for Many-Objective Optimization by Zhang, Xingyi, Tian, Ye, Jin, Yaochu

“…Evolutionary algorithms (EAs) have shown to be promising in solving many-objective optimization problems (MaOPs), where the performance of these algorithms…”
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A Survey of Deep Learning Applications to Autonomous Vehicle Control by Kuutti, Sampo, Bowden, Richard, Jin, Yaochu, Barber, Phil, Fallah, Saber

“…Designing a controller for autonomous vehicles capable of providing adequate performance in all driving scenarios is challenging due to the highly complex…”
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A Kriging-Assisted Two-Archive Evolutionary Algorithm for Expensive Many-Objective Optimization by Song, Zhenshou, Wang, Handing, He, Cheng, Jin, Yaochu

“…Only a small number of function evaluations can be afforded in many real-world multiobjective optimization problems (MOPs) where the function evaluations are…”
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A Strengthened Dominance Relation Considering Convergence and Diversity for Evolutionary Many-Objective Optimization by Tian, Ye, Cheng, Ran, Zhang, Xingyi, Su, Yansen, Jin, Yaochu

“…Both convergence and diversity are crucial to evolutionary many-objective optimization, whereas most existing dominance relations show poor performance in…”
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Evolutionary multi-objective generation of recurrent neural network ensembles for time series prediction by Smith, Christopher, Jin, Yaochu

“…Ensembles have been shown to provide better generalization performance than single models. However, the creation, selection and combination of individual…”
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An Efficient Approach to Nondominated Sorting for Evolutionary Multiobjective Optimization by Xingyi Zhang, Ye Tian, Ran Cheng, Yaochu Jin

“…Evolutionary algorithms have been shown to be powerful for solving multiobjective optimization problems, in which nondominated sorting is a widely adopted…”
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A Surrogate-Assisted Reference Vector Guided Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization by Chugh, Tinkle, Jin, Yaochu, Miettinen, Kaisa, Hakanen, Jussi, Sindhya, Karthik

“…We propose a surrogate-assisted reference vector guided evolutionary algorithm (EA) for computationally expensive optimization problems with more than three…”
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Artificial intelligence in recommender systems by Zhang, Qian, Lu, Jie, Jin, Yaochu

“…Recommender systems provide personalized service support to users by learning their previous behaviors and predicting their current preferences for particular…”
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From federated learning to federated neural architecture search: a survey by Zhu, Hangyu, Zhang, Haoyu, Jin, Yaochu

“…Federated learning is a recently proposed distributed machine learning paradigm for privacy preservation, which has found a wide range of applications where…”
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Feature selection for high-dimensional classification using a competitive swarm optimizer by Gu, Shenkai, Cheng, Ran, Jin, Yaochu

“…When solving many machine learning problems such as classification, there exists a large number of input features. However, not all features are relevant for…”
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A Multiobjective Evolutionary Algorithm Using Gaussian Process-Based Inverse Modeling by Ran Cheng, Yaochu Jin, Narukawa, Kaname, Sendhoff, Bernhard

“…To approximate the Pareto front, most existing multiobjective evolutionary algorithms store the nondominated solutions found so far in the population or in an…”
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Surrogate-Assisted Cooperative Swarm Optimization of High-Dimensional Expensive Problems by Sun, Chaoli, Jin, Yaochu, Cheng, Ran, Ding, Jinliang, Zeng, Jianchao

“…Surrogate models have shown to be effective in assisting metaheuristic algorithms for solving computationally expensive complex optimization problems. The…”
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Committee-Based Active Learning for Surrogate-Assisted Particle Swarm Optimization of Expensive Problems by Handing Wang, Yaochu Jin, Doherty, John

“…Function evaluations (FEs) of many real-world optimization problems are time or resource consuming, posing a serious challenge to the application of…”
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Surrogate-assisted hierarchical particle swarm optimization by Yu, Haibo, Tan, Ying, Zeng, Jianchao, Sun, Chaoli, Jin, Yaochu

“…Meta-heuristic algorithms, which require a large number of fitness evaluations before locating the global optimum, are often prevented from being applied to…”
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