Vermont EPSCoR Publications and Products


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2016
Hanley JP, Eppstein MJ, Buzas JS, Rizzo DM. Evolving Probabilistically Significant Epistatic Classification Rules for Heterogeneous Big Data Sets. In: Genetic and Evolutionary Computation Conference (GECCO 2016). Genetic and Evolutionary Computation Conference (GECCO 2016). Denver, CO; 2016. Available from: http://gecco-2016.sigevo.org/index.html/Papers
2012
Manukyan N, Eppstein MJ, Rizzo DM. Data-Driven Cluster Reinforcement and Visualization in Sparsely-Matched Self-Organizing Maps. IEEE Transactions on Neural Networks and Learning Systems [Internet]. 2012 ;23(5):846 - 852. Available from: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6178802
Manukyan N, Eppstein MJ, Horbar JD, Leahy KA, Kenny MJ, Mukherjee S, Rizzo DM. Evolutionary Mining for Multivariate Associations in Large Time-varying Dataset: A Healthcare Network Application. In: Genetic and Evolutionary Computation Conference (GECCO). Genetic and Evolutionary Computation Conference (GECCO). ; 2012.
Krupa JS, Chatterjee S, Eldridge E, Rizzo DM, Eppstein MJ. Feature Selection for Classification: A Plug-In Hybrid Vehicle Adoption Application. In: Genetic and Evolutionary Computation Conference (GECCO). Genetic and Evolutionary Computation Conference (GECCO). Philadelphia, PA; 2012. pp. 1111-1118.
2007
Payne JL, Eppstein MJ, Goodnight CJ. Sensitivity of Self-Organized Speciation to Long-Disctance Dispersal. In: 2007 IEEE Symposium on Artificial Life2007 IEEE Symposium on Artificial Life. 2007 IEEE Symposium on Artificial Life2007 IEEE Symposium on Artificial Life. Honolulu, HI, USA: IEEE; 2007. pp. 1 - 7. Available from: http://www.cs.uvm.edu/~meppstei/personal/Payne_Speciation_IEEE07_aspublished.pdf