Selected Publictions of David Helmbold

Object Detection and Terrain Classification
Other Learning Applications
Boosting
On-line Learning
Learning Theory
Computer Go
Debugging of Parallel Programs
Parallel Algorithms


Object Detection and Terrain Classification

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.

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.

S. Lodha, D. Fitzpatrick, and D.P. Helmbold. Aerial lidar data classification using expectation-maximization. In Proceedings of SPIE Conference on Vision Geometry XIV, volume 6499, January 2007.

O. Wang, S. Lodha, and D.P. Helmbold. A bayesian approach to building footprint extraction from aerial lidar data. In Proceedings of the Third International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT). IEEE, 2006.

S. Lodha, E. Krepps, D.P. Helmbold, and D. Fitzpatrick. Aerial lidar data classification using support vector machines (svm). In Proceedings of the Third International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT). IEEE, 2006.

Other Learning Applications

G. Grindlay and D.P. Helmbold. Modeling, analyzing, and synthesizing expressive piano performances with graphical models. Machine Learning, 2006 \newblock In press, published on-line by Springer, June 2006.

D.P. Helmbold, D.D.E. Long, T. L. Sconyers, and B. Sherrod. Adaptive disk spin-down for mobile computers. Mobile Networks \& Applications (MONET), vol. 5, no. 4, pages 285--298, December 2000.

Boosting

Nigel Duffy and David Helmbold. Boosting methods for regression. Machine Learning, vol. 47, no. 2-3, pages 153--200, May-June 2002. (Conference version appeared in COLT 2000)

Nigel Duffy and David Helmbold. A geometric approach to leveraging weak learners. Theoretical Computer Science, vol. 284, pages 67--108, 2002. (Conference version appeared in EuroColt, March 1999)

N. Duffy and D.P. Helmbold. Potential boosters?. In Klaus-Robert Muller Sara Solla, Todd Leen, editor, Neural Information Processing Systems: Natural and Synthetic (NIPS'1999), pages 258--264. MIT Press, 2000.

On-line Learning

David Helmbold and Manfred K. Warmuth. Learning permutations with exponential weights. Journal of Machine Learning Research, vol. 10, pages 1687--1718, July 2009.

D.P. Helmbold, S. Panizza, and M.K. Warmuth. Direct and indirect algorithms for on-line learning of disjunctions. Theoretical Computer Science, vol. 284, no. 1, pages 109--142, 2002.

D.P. Helmbold, N. Littlestone, and P. Long. Apple tasting. Information and Computation, vol. 161, no. 2, pages 85--139, sep 2000.

D.P. Helmbold, N. Littlestone, and P. Long. On-line learning with linear loss constraints. Information and Computation, vol. 161, no. 2, pages 140--171, sep 2000.

D.P. Helmbold, J. Kivinen, and M.K. Warmuth. Relative loss bounds for single neurons. IEEE Transactions on Neural Networks, vol. 6, no. 10, pages 1291--1304, Nov 1999.

D.P. Helmbold, R.E. Schapire, Y. Singer, and M.K. Warmuth. On-line portfolio selection using multiplicative updates. Mathematical Finance, vol. 8, no. 4, pages 325--347, 1998.

N. Cesa-Bianchi, D.P. Helmbold, and S. Panizza. On bayes methods for on-line boolean prediction. Algorithmica, vol. 22, no. 1/2, pages 112--137, 1998.

D.P. Helmbold and S. Panizza. Some label efficient learning results. In Proceedings of the Tenth Annual Conference on Computational Learning Theory, pages 218--230. ACM Press, July 1997.

N. Cesa-Bianchi, Y. Freund, D.P. Helmbold, D. Haussler, R.E. Schapire, and M.K. Warmuth. How to use expert advice. Journal of the ACM, vol. 44, no. 3, pages 427--485, 1997.

D.P. Helmbold and R.E. Schapire. Predicting nearly as well as the best pruning of a decision tree. Machine Learning, vol. 27, no. 1, pages 51--68, April 1997.

N. Cesa-Bianchi, Y. Freund, D.P. Helmbold, and M.K. Warmuth. On-line prediction and conversion strategies. Machine Learning, vol. 25, no. 1, pages 71--110, October 1996.

Learning Theory

C. Gentile and D.P. Helmbold. Improved lower bounds for learning from noisy examples: an information-theoretic approach. Information and Computation, vol. 166, no. 2, may 2001.

D.P. Helmbold, R.E. Schapire, Y. Singer, and M.K. Warmuth. A comparison of new and old algorithms for a mixture estimation problem. Machine Learning, vol. 27, no. 1, pages 97--119, April 1997.

D.P. Helmbold and M.K. Warmuth. On weak learning. Journal of Computer and System Sciences, vol. 50, no. 3, pages 551--573, June 1995.

D.P. Helmbold and P.M. Long. Tracking drifting concepts by minimizing disagreements. Machine Learning, vol. 14, no. 1, pages 27--45, January 1994.

D.P. Helmbold, R. Sloan, and M.K. Warmuth. Learning integer lattices. SIAM J. Comput., vol. 21, no. 2, pages 240--266, April 1992.

D.P. Helmbold, R. Sloan, and M.K. Warmuth. Learning nested differences of intersection closed concept classes. Machine Learning, vol. 5, no. 2, pages 165--196, June 1990.

Computer Go

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.

Debugging of Parallel Programs

D.P. Helmbold and C.E. McDowell. Debugging and Performance Tuning for Parallel Computing Systems, chapter Race Detection -- Ten Years Later. IEEE Computer Society Press, 1996.

D.P. Helmbold and C.E. McDowell. A taxonomy of race conditions. Journal of Parallel and Distributed Computing, vol. 33, no. 2, pages 159--164, March 1996.

D.P. Helmbold, C.E. McDowell, and J-Z. Wang. Determining possible event orders by analyzing sequential traces. IEEE Transactions on Parallel and Distributed Systems, vol. 4, no. 7, pages 827--840, July 1993.

D.P. Helmbold and C.E. McDowell. Modeling speedup ($n$) greater than $n$. IEEE Transactions on Parallel and Distributed Systems, vol. 1, no. 2, pages 250--256, August 1990.

D.P. Helmbold and C.E. McDowell. Debugging concurrent programs. ACM Computing Surveys, vol. 21, no. 4, pages 593--622, December 1989. (Translated for the April 1991 Japanese language issue of Bit).

D.P. Helmbold and D. Luckham. Debugging ada tasking programs. IEEE Software, vol. 2, no. 2, pages 47--57, March 1985.

Parallel Algorithms

D.P. Helmbold and E. Mayr. Fast scheduling algorithms on parallel computers. Advances in Computing Research, vol. 4, pages 39--68, 1987.

D.P. Helmbold and E. Mayr. Two processor scheduling is in NC. SIAM Journal on Computing, vol. 16, no. 4, pages 747--759, August 1987.