Joseph Reisinger
Machine Learning Lab: Ph.D. Alumni
Neural Networks Lab: Formerly affiliated Ph.D. Student, Undergraduate Alumni
Joe's work with the NNRG focused on evolvability, modularity and indirect encoding in evolutionary computation. He later completed a PhD with the Machine Learning group, working on lexical semantics.
Homepage:
http://www.cs.utexas.edu/~joeraii
Publications
     [Expand to show all 15][Minimize]
Latent Variable Models of Distributional Lexical Semantics 2012
Joseph Reisinger, PhD Thesis, Department of Computer Science, University of Texas at Austin.
Cross-Cutting Models of Lexical Semantics 2011
Joseph Reisinger and Raymond Mooney, In Proceedings of The Conference on Empirical Methods in Natural Language Processing (EMNLP 2011), pp. 1405-1415, July 2011.
Fine-Grained Class Label Markup of Search Queries 2011
Joseph Reisinger and Marius Pasca, In Proceedings of The 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-HLT 2011), pp. 1200-1209, June 2011.
A Mixture Model with Sharing for Lexical Semantics 2010
Joseph Reisinger and Raymond J. Mooney, In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-2010), pp. 1173--1182, MIT, Massachusetts, USA, October 9--11 2010.
Cross-cutting Models of Distributional Lexical Semantics 2010
Joseph S. Reisinger, unpublished. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
Multi-Prototype Vector-Space Models of Word Meaning 2010
Joseph Reisinger, Raymond J. Mooney, In Proceedings of the 11th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-2010), pp. 109-117 2010.
Spherical Topic Models 2010
Joseph Reisinger, Austin Waters, Bryan Silverthorn, and Raymond J. Mooney, In Proceedings of the 27th International Conference on Machine Learning (ICML 2010) 2010.
Spherical Topic Models 2009
Joseph Reisinger, Austin Waters, Bryan Silverthorn, and Raymond Mooney, In NIPS'09 workshop: Applications for Topic Models: Text and Beyond 2009.
Online Kernel Selection for Bayesian Reinforcement Learning 2008
Joseph Reisinger, Peter Stone, and Risto Miikkulainen, In Proceedings of the Twenty-Fifth International Conference on Machine Learning, July 2008.
Acquiring Evolvability through Adaptive Representations 2007
Joseph Reisinger and Risto Miikkulainen, In Proceeedings of the Genetic and Evolutionary Computation Conference, pp. 1045-1052 2007.
Coevolving Strategies for General Game Playing 2007
Joseph Reisinger, Erkin Bahceci, Igor Karpov and Risto Miikkulainen, In Proceedings of the {IEEE} Symposium on Computational Intelligence and Games, pp. 320-327, Piscataway, NJ 2007. IEEE.
Selecting for Evolvable Representations 2006
Joseph Reisinger and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference 2006.
Towards an Empirical Measure of Evolvability 2005
Joseph Reisinger, Kenneth O. Stanley, Risto Miikkulainen, In Genetic and Evolutionary Computation Conference {(GECCO2005)} Workshop Program, pp. 257-264, Washington, D.C. 2005. ACM Press.
Evolving Reusable Neural Modules 2004
Joseph Reisinger, Kenneth O. Stanley, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference 2004.
Exploiting Morphological Conventions for Genetic Reuse 2004
Kenneth O. Stanley, Joseph Reisinger, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference ({GECCO}-2004) Workshop Program, Berlin 2004. Springer Verlag.
Projects
Leveraging Evolvability in Search 2004 - 2007
NEAT: Evolving Increasingly Complex Neural Network Topologies 2000 - 2011
Areas of Interest
Evolutionary Computation Game Playing Neuroevolution Reinforcement Learning
Labs
Formerly affiliated with Machine Learning Formerly affiliated with Neural Networks