Visualization System for Evolutionary Neural Networks for Deep Learning
作者： Junghoon Chae , Catherine D Schuman , Steven R Young , J Travis Johnston , Derek C Rose
DOI: 10.1109/BIGDATA47090.2019.9006470
关键词:
摘要: Deep learning is actively used in a wide range of fields for scientific discovery. To effectively apply deep learning to a particular problem, it is important to select an appropriate network …
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osti.gov 参考文章(13)
John H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence Ann Arbor: University of Michigan Press. ,(1992) , 10.7551/MITPRESS/1090.001.0001
Humera Farooq, Nordin Zakaria, Muhammad Tariq Siddique, An Interactive Visualization of Genetic Algorithm on 2-D Graph International Journal of Software Science and Computational Intelligence. ,vol. 4, pp. 34- 54 ,(2012) , 10.4018/JSSCI.2012010102
E. Hart, P. Ross, GAVEL - a new tool for genetic algorithm visualization IEEE Transactions on Evolutionary Computation. ,vol. 5, pp. 335- 348 ,(2001) , 10.1109/4235.942528
William B Shine, Christoph F Eick, Visualizing the evolution of genetic algorithm search processes ieee international conference on evolutionary computation. pp. 367- 372 ,(1997) , 10.1109/ICEC.1997.592337
Ji Soo Yi, Youn ah Kang, John Stasko, J.A. Jacko, Toward a Deeper Understanding of the Role of Interaction in Information Visualization IEEE Transactions on Visualization and Computer Graphics. ,vol. 13, pp. 1224- 1231 ,(2007) , 10.1109/TVCG.2007.70515
Thomas M. J. Fruchterman, Edward M. Reingold, Graph drawing by force-directed placement Software - Practice and Experience. ,vol. 21, pp. 1129- 1164 ,(1991) , 10.1002/SPE.4380211102
Steven R Young, Derek C Rose, Thomas P Karnowski, Seung-Hwan Lim, Robert M Patton, None, Optimizing deep learning hyper-parameters through an evolutionary algorithm ieee international conference on high performance computing data and analytics. pp. 4- ,(2015) , 10.1145/2834892.2834896
Nicholas Freitag McPhee, Maggie M. Casale, Mitchell Finzel, Thomas Helmuth, Lee Spector, Visualizing Genetic Programming Ancestries genetic and evolutionary computation conference. pp. 1419- 1426 ,(2016) , 10.1145/2908961.2931741
Risto Miikkulainen, Jason Liang, Elliot Meyerson, Aditya Rawal, Daniel Fink, Olivier Francon, Bala Raju, Hormoz Shahrzad, Arshak Navruzyan, Nigel Duffy, Babak Hodjat, Evolving Deep Neural Networks arXiv: Neural and Evolutionary Computing. pp. 293- 312 ,(2017) , 10.1016/B978-0-12-815480-9.00015-3
Tim Salimans, Jonathan Ho, Xi Chen, Szymon Sidor, Ilya Sutskever, Evolution Strategies as a Scalable Alternative to Reinforcement Learning. arXiv: Machine Learning. ,(2017)