DAVID P. HELMBOLD
Professor, Computer Science
Computer Science Department
E2 Building room 345B
University of California
Santa Cruz, CA 95064
There will be a machine learning summer school at Santa Cruz this July.
David Helmbold's current research centers around machine learning
and computational learning theory. In addition, to theoretical work,
he has applied learning algorithms to practical problems such as
determining when to spin down a disk drive in a portable computer
to save power and detecting small objects in images.
David P. Helmbold and Philip M. Long On the Necessity of Irrelevant Variables
in ICML 2011.
Manfred K. Warmuth, Wouter M. Koolen, and David P. Helmbold
Combining Initial Segments of Lists in ALT 2011.
Damian Eads, Edward Rosten, and David Helmbold.
Learning object location predictors with boosting and
grammer-guided feature extraction in Proceedings of the British
Machine Vision Conference (BMVC), September 2009.
David Helmbold and Aleatha Parker-Wood.
All-moves-as-first heuristics in monte-carlo go in Hamid R.
Arabnia, David de la Fuente, and Jose A. Olivas, editors, Proceedings of
the 2009 International Conference on Artificial Intelligence, pages
605--610. WorldComp, July 2009.
David Helmbold and Manfred K. Warmuth.
Learning Permutations with exponential weights
in Journal of Machine Learning Research, vol. 10, pages 1687--1718, July 2009.
(The conference version appeared in COLT 2007.)
S. Lodha, D. Fitzpatrick, and D. P. Helmbold.
Aerial lidar data classification using adaboost in
Proceedings of the 3D Digital Imaging and Modeling Conference (3DIM), pages
435--443, August 2007.
Here is a list containing many of my publications. It includes
work in the areas of Object Detection and Terrain classification, Computer Go, Boosting, On-line learning,
Other learning theory, and Learning Applications, as well as some older work on Debugging of Parallel Programs and
Last modified June 4, 2012 (09:37:37 AM).