Zimeng Lyu

According to our database, Zimeng Lyu authored at least 9 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

Efficient Neuroevolution Using Island Repopulation and Simplex Hyperparameter Optimization.

Aditya Shankar Thakur, Akshar Bajrang Awari, Zimeng Lyu, Travis Desell

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Co-evolving Recurrent Neural Networks and their Hyperparameters with Simplex Hyperparameter Optimization.

Amit Dilip Kini, Swaraj Sambhaji Yadav, Aditya Shankar Thakur, Akshar Bajrang Awari, Zimeng Lyu, Travis Desell

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

2022

ONE-NAS: an online neuroevolution based neural architecture search for time series forecasting.

Zimeng Lyu, Travis Desell

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

2021

Neuroevolution of recurrent neural networks for time series forecasting of coal-fired power plant operating parameters.

Zimeng Lyu, Shuchita Patwardhan, David Stadem, James Langfeld, Steven A. Benson, Seth Thoelke, Travis Desell

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Improving Distributed Neuroevolution Using Island Extinction and Repopulation.

Zimeng Lyu, Joshua Karns, AbdElRahman ElSaid, Mohamed Wiem Mkaouer, Travis Desell

Proceedings of the Applications of Evolutionary Computation, 2021

An Experimental Study of Weight Initialization and Lamarckian Inheritance on Neuroevolution.

Zimeng Lyu, AbdElRahman ElSaid, Joshua Karns, Mohamed Wiem Mkaouer, Travis Desell

Proceedings of the Applications of Evolutionary Computation, 2021

Continuous Ant-Based Neural Topology Search.

AbdElRahman ElSaid, Joshua Karns, Zimeng Lyu, Alexander G. Ororbia II, Travis Desell

Proceedings of the Applications of Evolutionary Computation, 2021

2020

Improving neuroevolutionary transfer learning of deep recurrent neural networks through network-aware adaptation.

AbdElRahman ElSaid, Joshua Karns, Zimeng Lyu, Daniel E. Krutz, Alexander Ororbia, Travis Desell

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

Neuro-Evolutionary Transfer Learning Through Structural Adaptation.

AbdElRahman ElSaid, Joshua Karnas, Zimeng Lyu, Daniel E. Krutz, Alexander G. Ororbia II, Travis Desell

Proceedings of the Applications of Evolutionary Computation - 23rd European Conference, 2020