Neuroscience Guide: Matthew Kretchmar

1. Kretchmar, R.M., & Zhao, Y. (March 2014) Text Message Authorship Classification Using Kernel Support Vector Machines. Computational Science and Computational Intelligence, CSCI '14. Las Vegas, NV.   
2. Kell, N., & Kretchmar, R. M. (2013). Suspense at the Ballot Box. College Mathematics Journal, 44(1), 9-16. doi:10.4169/college.math.j.44.1.009
3. Bucantanschi, D., Hoffmann, B., Hutson, K., & Kretchmar, R. (2007). A neighborhood search technique for the freeze tag problem. In E. K. Baker, A. Joseph, A. Mehrotra & M. A. Trick (Eds.), Extending the horizons: Advances in computing, optimization, and decision technologies (pp. 97-113). New York: Springer. doi:10.1007/978-0-387-48793-9_7   CONSORT    WorldCat
4. Feil, T., Hutson, K., & Kretchmar, R. M. (2005). Tree traversals and permutations. Congressus Numerantium. A Conference Journal on Numerical Themes, 172, 201-221.   MathSciNet   CiteSeer^x  
5. Anderson, C. W., Hittle, D., Kretchmar, M., & Young, P. (2004). Robust reinforcement learning for heating, ventilation, and air conditioning control of buildings. In J. Si (Ed.), Handbook of learning and approximate dynamic programming (pp. 517). Piscataway, NJ: IEEE Press : Wiley-Interscience.  CONSORT  WorldCat
6. Anderson, C. W., Kretchmar, M., Young, P., & Hittle, D. (2004). Robust reinforcement learning using integral-quadratic constraints. In J. Si (Ed.), Handbook of learning and approximate dynamic programming (pp. 337). Piscataway, NJ: IEEE Press : Wiley-Interscience.  CONSORT  WorldCat
7. Kretchmar, R. M., Feil, T., & Bansal, R. (2003). Improved automatic discovery of subgoals for options in hierarchical reinforcement learning. Journal of Computer Science and Technology, 3(2), 9-14.  Article

Matt Kretchmar

Faculty  |  Computer Science, Mathematics, Neuroscience

Associate Professor

F.W. Olin Science Hall

207

kretchmar@denison.edu

740-587-6721

Personal Website