Daniel L. Elliott Contact Information: Email: id@cs.colostate.edu, id:dane Twitter: dan elliott ster (all one word)
		Hard at work...

About Me:

Some of my qualifications can be viewed in my resume.

My research, interests, and current work:

• Modular reinforcement learning:
• Neural Networks:
• Computer Vision:
• Covariance regularization:
  • Interests: random projections and classification, MPPCA
  • D.L. Elliott, C. Anderson, M. Kirby "Covariance Regularization for Supervised Learning in High Dimensions," Proceedings of ANNIE 2010, November 1, 2010. (pdf)
  • D.L. Elliott (2009). "Covariance Regularization In Mixture Of Gaussians For High-Dimensional Image Classification". MS Thesis, Colorado State University. (pdf)
  • B. Draper, D.L. Elliott, J. Hayes, and K. Baek. " EM in High Dimensional Spaces ", IEEE Transactions on Systems, Man and Cybernetics, 35(3):571-577, June 2005. (pdf)
• Modelling grain drying and storage data:
  • Current: Predicting seed drying times in forced-air seed drying buildings with heated air.
  • D.L. Elliott, R.E. Valentine "Recurrent Neural Networks for moisture content prediction in seed corn dryer buildings," Proceedings of ICTAI 2011, November 7, 2011. (pdf|ps). Accompanying poster: (pdf|ps).
    • ESN and Elman implementation based off code written by Elliott Forney.
• Other:
  • L.Elliott, D.Elliott, L.R.Forbringer "Using HR metrics to make a difference" in Jac Fitz-enz, ed., The New HR Analytics: Predicting the Economic Value of Your Companies Human Capital Investments, 2010.

Code and data sets

• Image data used in many covariance regularization experiments: preprocessed to 32x32 and grayscale.
• The PyMix package. PyMix is a Python package for mixture models. I have contributed a little code to this excellent package. In particular, I added the ability to run the algorithm layed out in the ANNIE 2010 paper.
• Code I use with the SNOW package in R (much credit belongs to Andrew Sutton): snowfarm.R example.

Other stuff:

• For more information: Exoteric Analytics
• PicoLisp. Even though the people leading developent use VIM, it is still a great Lisp variant.
• Python stuff:
  • SciPy.
  • PyMix.
  • PyBrain.
  • Where Ubuntu users can install v1.0 of matplotlib. Ubuntu is currently at 0.9 or something like that.
• My beloved EMACS:
  • TRAMP mode.
  • Article about Eshell.
• Latex:
  • AMSmath documentation.
• Ever thought of becomming a Catholic or returning to the Church? It's totally rad.
• Our University parish.
• A great accompanyment to the Gospel: "hope for the flowers"

Background obtained from: www.boogiejack.com

Last updated September 2011