李振华
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于2019年加入南京航空航天大学计算机科学与技术学院,现为学院副研究员. 从事最优化和机器学习学习等方面的研究工作,在国际顶级期刊和会议发表论文10余篇。科研项目:现承担国家自然科学基金青年项目和江苏省自然科学基金青年项目各一项.入选江苏省\研究领域
最优化方法,机器学习"最优化方法和机器学习近期论文
[1] An Efficient Elitist Covariance Matrix Adaptation for Continuous Local Search in High Dimension[2] An Efficient Rank-1 Update for Cholesky CMA-ES Using Auxiliary Evolution Path.2017 IEEE Congress on Evolutionary Computation[3] What does the Evolution Path Learn in CMA-ES?.14th International Conference on Parallel Problem Solving from Nature (PPSN)[4] Integrating Preference by Means of Desirability Function with Evolutionary Multi-objective Optimization.Intelligent Automation & Soft Computing[5] Pareto Multi-Task Learning.33rd Conference on Neural Information Processing Systems (NeurIPS 2019)[6] Evolution strategies for continuous optimization: A survey of the state-of-the-art.Swarm and Evolutionary Computation[7] Variable Metric Evolution Strategies by Mutation Matrix Adaptation.Information Sciences[8] Fast Covariance Matrix Adaptation for Large-Scale Black-Box Optimization.IEEE Transactions on Cybernetics[9] A simple yet efficient evolution strategy for large scale black-box optimization[J].IEEE Transactions on Evolutionary Computation 相关热点
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