2007 |
54 | EE | David P. Helmbold,
Manfred K. Warmuth:
Learning Permutations with Exponential Weights.
COLT 2007: 469-483 |
2006 |
53 | EE | Oliver Wang,
Suresh K. Lodha,
David P. Helmbold:
A Bayesian Approach to Building Footprint Extraction from Aerial LIDAR Data.
3DPVT 2006: 192-199 |
52 | EE | Suresh K. Lodha,
Edward J. Kreps,
David P. Helmbold,
Darren Fitzpatrick:
Aerial LiDAR Data Classification Using Support Vector Machines (SVM).
3DPVT 2006: 567-574 |
51 | EE | Graham Grindlay,
David P. Helmbold:
Modeling, analyzing, and synthesizing expressive piano performance with graphical models.
Machine Learning 65(2-3): 361-387 (2006) |
2002 |
50 | | Nigel Duffy,
David P. Helmbold:
Boosting Methods for Regression.
Machine Learning 47(2-3): 153-200 (2002) |
49 | EE | David P. Helmbold,
Sandra Panizza,
Manfred K. Warmuth:
Direct and indirect algorithms for on-line learning of disjunctions.
Theor. Comput. Sci. 284(1): 109-142 (2002) |
48 | EE | Nigel Duffy,
David P. Helmbold:
A geometric approach to leveraging weak learners.
Theor. Comput. Sci. 284(1): 67-108 (2002) |
2001 |
47 | | David P. Helmbold,
Bob Williamson:
Computational Learning Theory, 14th Annual Conference on Computational Learning Theory, COLT 2001 and 5th European Conference on Computational Learning Theory, EuroCOLT 2001, Amsterdam, The Netherlands, July 16-19, 2001, Proceedings
Springer 2001 |
2000 |
46 | | Nigel Duffy,
David P. Helmbold:
Leveraging for Regression.
COLT 2000: 208-219 |
45 | | David P. Helmbold,
Nick Littlestone,
Philip M. Long:
On-Line Learning with Linear Loss Constraints.
Inf. Comput. 161(2): 140-171 (2000) |
44 | | David P. Helmbold,
Nick Littlestone,
Philip M. Long:
Apple Tasting.
Inf. Comput. 161(2): 85-139 (2000) |
43 | | David P. Helmbold,
Darrell D. E. Long,
Tracey L. Sconyers,
Bruce Sherrod:
Adaptive disk spin-down for mobile computers.
MONET 5(4): 285-297 (2000) |
1999 |
42 | EE | David P. Helmbold,
Sandra Panizza,
Manfred K. Warmuth:
Direct and Indirect Algorithms for On-line Learning of Disjunctions.
EuroCOLT 1999: 138-152 |
41 | EE | Nigel Duffy,
David P. Helmbold:
A Geometric Approach to Leveraging Weak Learners.
EuroCOLT 1999: 18-33 |
40 | EE | Nigel Duffy,
David P. Helmbold:
Potential Boosters?
NIPS 1999: 258-264 |
39 | EE | David P. Helmbold,
Jyrki Kivinen,
Manfred K. Warmuth:
Relative loss bounds for single neurons.
IEEE Transactions on Neural Networks 10(6): 1291-1304 (1999) |
1998 |
38 | EE | Claudio Gentile,
David P. Helmbold:
Improved Lower Bounds for Learning from Noisy Examples: An Information-Theoretic Approach.
COLT 1998: 104-115 |
37 | | Nicolò Cesa-Bianchi,
David P. Helmbold,
Sandra Panizza:
On Bayes Methods for On-Line Boolean Prediction.
Algorithmica 22(1/2): 112-137 (1998) |
1997 |
36 | EE | David P. Helmbold,
Sandra Panizza:
Some Label Efficient Learning Results.
COLT 1997: 218-230 |
35 | | David P. Helmbold,
Stephen Kwek,
Leonard Pitt:
Learning When to Trust Which Experts.
EuroCOLT 1997: 134-149 |
34 | EE | Nicolò Cesa-Bianchi,
Yoav Freund,
David Haussler,
David P. Helmbold,
Robert E. Schapire,
Manfred K. Warmuth:
How to use expert advice.
J. ACM 44(3): 427-485 (1997) |
33 | | David P. Helmbold,
Robert E. Schapire:
Predicting Nearly As Well As the Best Pruning of a Decision Tree.
Machine Learning 27(1): 51-68 (1997) |
32 | | David P. Helmbold,
Robert E. Schapire,
Yoram Singer,
Manfred K. Warmuth:
A Comparison of New and Old Algorithms for a Mixture Estimation Problem.
Machine Learning 27(1): 97-119 (1997) |
1996 |
31 | EE | Nicolò Cesa-Bianchi,
David P. Helmbold,
Sandra Panizza:
On Bayes Methods for On-Line Boolean Prediction.
COLT 1996: 314-324 |
30 | | David P. Helmbold,
Robert E. Schapire,
Yoram Singer,
Manfred K. Warmuth:
On-Line Portfolio Selection Using Multiplicative Updates.
ICML 1996: 243-251 |
29 | EE | David P. Helmbold,
Darrell D. E. Long,
Bruce Sherrod:
A Dynamic Disk Spin-Down Technique for Mobile Computing.
MOBICOM 1996: 130-142 |
28 | | David P. Helmbold,
Charles E. McDowell:
A Class of Synchronization Operations that Permit Efficient Race Detection.
PDPTA 1996: 1537-1548 |
27 | | David P. Helmbold,
Charles E. McDowell:
A Taxonomy of Race Conditions.
J. Parallel Distrib. Comput. 33(2): 159-164 (1996) |
26 | | Nicolò Cesa-Bianchi,
Yoav Freund,
David P. Helmbold,
Manfred K. Warmuth:
On-line Prediction and Conversion Strategies.
Machine Learning 25(1): 71-110 (1996) |
1995 |
25 | EE | David P. Helmbold,
Robert E. Schapire:
Predicting Nearly as Well as the Best Pruning of a Decision Tree.
COLT 1995: 61-68 |
24 | EE | David P. Helmbold,
Yoram Singer,
Robert E. Schapire,
Manfred K. Warmuth:
A Comparison of New and Old Algorithms for a Mixture Estimation Problem.
COLT 1995: 69-78 |
23 | EE | David P. Helmbold,
Jyrki Kivinen,
Manfred K. Warmuth:
Worst-case Loss Bounds for Single Neurons.
NIPS 1995: 309-315 |
22 | | David P. Helmbold,
Manfred K. Warmuth:
On Weak Learning.
J. Comput. Syst. Sci. 50(3): 551-573 (1995) |
1994 |
21 | | David P. Helmbold,
Philip M. Long:
Tracking Drifting Concepts By Minimizing Disagreements.
Machine Learning 14(1): 27-45 (1994) |
1993 |
20 | EE | Nicolò Cesa-Bianchi,
Yoav Freund,
David P. Helmbold,
David Haussler,
Robert E. Schapire,
Manfred K. Warmuth:
How to use expert advice.
STOC 1993: 382-391 |
19 | EE | David P. Helmbold,
Charles E. McDowell,
Jian-Zhong Wang:
Determining Possible Event Orders by Analyzing Sequential Traces.
IEEE Trans. Parallel Distrib. Syst. 4(7): 827-840 (1993) |
1992 |
18 | EE | David P. Helmbold,
Manfred K. Warmuth:
Some Weak Learning Results.
COLT 1992: 399-412 |
17 | | David P. Helmbold,
Nick Littlestone,
Philip M. Long:
Apple Tasting and Nearly One-Sided Learning
FOCS 1992: 493-502 |
16 | | David P. Helmbold,
Robert H. Sloan,
Manfred K. Warmuth:
Learning Integer Lattices.
SIAM J. Comput. 21(2): 240-266 (1992) |
1991 |
15 | EE | David P. Helmbold,
Philip M. Long:
Tracking Drifting Concepts Using Random Examples.
COLT 1991: 13-23 |
14 | | David P. Helmbold,
Charles E. McDowell:
Computing Reachable States of Parallel Programs.
Workshop on Parallel and Distributed Debugging 1991: 76-84 |
1990 |
13 | EE | David P. Helmbold,
Robert H. Sloan,
Manfred K. Warmuth:
Learning Integer Lattices.
COLT 1990: 288-302 |
12 | | David P. Helmbold,
Charles E. McDowell,
Jian-Zhong Wang:
Analyzing Traces with Anonymous Synchronization.
ICPP (2) 1990: 70-77 |
11 | EE | David P. Helmbold,
Charles E. McDowell:
Modeling Speedup (n) Greater than n.
IEEE Trans. Parallel Distrib. Syst. 1(2): 250-256 (1990) |
10 | | David P. Helmbold,
Robert H. Sloan,
Manfred K. Warmuth:
Learning Nested Differences of Intersection-Closed Concept Classes.
Machine Learning 5: 165-196 (1990) |
1989 |
9 | EE | David P. Helmbold,
Robert H. Sloan,
Manfred K. Warmuth:
Learning Nested Differences of Intersection-Closed Concept Classes.
COLT 1989: 41-56 |
8 | | David P. Helmbold,
Charles E. McDowell:
Modeling Speedup greater than n.
ICPP (3) 1989: 219-225 |
7 | | Charles E. McDowell,
David P. Helmbold:
Debugging Concurrent Programs.
ACM Comput. Surv. 21(4): 593-622 (1989) |
1987 |
6 | | David C. Luckham,
David P. Helmbold,
D. L. Bryan,
M. A. Haberler:
Task Sequencing Language for Specifying Distributed Ada Systems.
PARLE (2) 1987: 444-463 |
5 | | David P. Helmbold,
Ernst W. Mayr:
Two Processor Scheduling is in NC.
SIAM J. Comput. 16(4): 747-759 (1987) |
1986 |
4 | | David P. Helmbold,
Ernst W. Mayr:
Two Processor Scheduling is in NC.
Aegean Workshop on Computing 1986: 12-25 |
3 | | David P. Helmbold,
Ernst W. Mayr:
Perfect Graphs and Parallel Algorithms.
ICPP 1986: 853-860 |
2 | | David C. Luckham,
David P. Helmbold,
Sigurd Meldal,
D. L. Bryan,
M. A. Haberler:
Task Sequencing Languages for Specifying Distributed Ada Systems.
System Development and Ada 1986: 249-305 |
1 | | David P. Helmbold,
Ernst W. Mayr:
Applications of Parallel Scheduling to Perfect Graphs.
WG 1986: 188-203 |