Elliot Meyerson
Ph.D. Alumni
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Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription 2020
Olivier Francon, Santiago Gonzalez, Babak Hodjat, Elliot Meyerson, Risto Miikkulainen, Xin Qiu, Hormoz Shahrzad, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2020), 2020.
From Prediction to Prescription: AI-Based Optimization of Non-Pharmaceutical Interventions for the COVID-19 Pandemic 2020
Risto Miikkulainen, Olivier Francon, Elliot Meyerson, Xin Qiu, Elisa Canzani, Babak Hodjat, arxiv:2005.13766 (2020).
From Prediction to Prescription: AI-Based Optimization of Non-Pharmaceutical Interventions for the COVID-19 Pandemic 2020
Risto Miikkulainen, Olivier Francon, Elliot Meyerson, Xin Qiu, Elisa Canzani, Babak Hodjat, arxiv:2005.13766 (2020).
Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel 2020
Xin Qiu, Elliot Meyerson, Risto Miikkulainen, In International Conference on Learning Representations, 2020.
Evolutionary Neural AutoML for Deep Learning 2019
Jason Liang, Elliot Meyerson, Babak Hodjat, Dan Fink, Karl Mutch, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2019) 2019.
Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains 2019
Elliot Meyerson and Risto Miikkulainen, In 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), 2019.
Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering 2018
Elliot Meyerson and Risto Miikkulainen, In Proceedings of the Sixth International Conference on Learning Representations (ICLR), Vancouver, Canada 2018.
Discovering Multi-Purpose Modules through Deep Multitask Learning 2018
Elliot Meyerson, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Evolutionary Architecture Search For Deep Multitask Networks 2018
Jason Liang, Elliot Meyerson, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pp. 8, Kyoto, Japan, July 2018.
Evolving Deep Neural Networks 2018
Risto Miikkulainen, Jason Liang, Elliot Meyerson, Aditya Rawal, Dan Fink, Olivier Francon, Bala Raju, Hormoz Shahrzad, Arshak Navruzyan, Nigel Duffy, and Babak Hodjat, In Artificial Intelligence in the Age of Neural Networks and Brain Computing, Robert Kozma, Cesare Alippi, Yoonsuck Choe, and Francesco Carlo Morabito (Eds.) 2018. Amsterdam: Elsevier.
Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing---and Back 2018
Elliot Meyerson, Risto Miikkulainen, In Proceedings of the 35th International Conference on Machine Learning 2018.
Discovering Evolutionary Stepping Stones through Behavior Domination 2017
Elliot Meyerson and Risto Miikkulainen, To Appear In Proceedings of The Genetic and Evolutionary Computation Conference (GECCO 2017), Berlin, Germany, July 2017. ACM. nominated for Best Paper Award.
Learning Behavior Characterizations for Novelty Search 2016
Elliot Meyerson, Joel Lehman and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2016), Denver, Colorado 2016. ACM.
Reuse of Neural Modules for General Video Game Playing 2016
Alexander Braylan, Mark Hollenbeck, Elliot Meyerson and Risto Miikkulainen, To Appear In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16) 2016.
Frame Skip Is a Powerful Parameter for Learning to Play Atari 2015
Alexander Braylan, Mark Hollenbeck, Elliot Meyerson and Risto Miikkulainen, In AAAI-15 Workshop on Learning for General Competency in Video Games 2015.
On the Cross-Domain Reusability of Neural Modules for General Video Game Playing 2015
Alexander Braylan, Mark Hollenbeck, Elliot Meyerson and Risto Miikkulainen, In IJCAI'15 Workshop on General Intelligence in Game-Playing Agents, pp. 7--14 2015.
Formerly affiliated with Neural Networks