神戸大学CMDS先端セミナー
神戸大学CMDS先端セミナーでは、データサイエンスやAIの分野で先端を走られている研究者から、最新の研究内容についてご紹介いただきます。主に、学部4回生・大学院生・教員を対象としていますが、どなたでも聴講できますのでお気軽にご参加ください。
開催内容
第6回 神戸大学CMDS先端セミナー
- タイトル
- The State of the Art of Collaborative Neurodynamic Optimization
- 講演者
- Prof. Jun Wang (Department of Computer Science & School of Data Science, City University of Hong Kong)
- 日時
- 2024年5月27日（月） 15:00-16:00
- 場所
- 工学研究科 LR-402 教室
- 概要
- The past four decades witnessed the birth and growth of neurodynamic optimization, which has emerged as a potentially powerful problem-solving tool for constrained optimization due to its inherent nature of biological plausibility and parallel and distributed information processing. Despite the success, almost all existing neurodynamic approaches a few years ago worked well only for optimization problems with convex or generalized convex functions. Effective neurodynamic approaches to optimization problems with nonconvex functions and discrete variables are rarely available. In this talk, the advances in neurodynamic optimization will be presented. Specifically, In the proposed collaborative neurodynamic optimization framework, multiple neurodynamic optimization models with different initial states are employed for scattered searches. In addition, a meta-heuristic rule in swarm intelligence (such as PSO) is used to reposition neuronal searches upon their local convergence to escape local minima toward global optima. Problem formulations and experimental results will be elaborated to substantiate the viability and efficacy of several specific paradigms in this framework for supervised/semi-supervised feature selection, supervised learning, vehicle-task assignment, model predictive control, energy load dispatching, and financial portfolio selection.
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