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ORCIDDavid P. Helmbold
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2020 – today
- 2020
[c46]Yang Liu, David P. Helmbold:
Online Learning Using Only Peer Prediction. AISTATS 2020: 2032-2042
2010 – 2019
- 2019
- [j30]Atsuyoshi Nakamura, David P. Helmbold, Manfred K. Warmuth:
Mistake bounds on the noise-free multi-armed bandit game. Inf. Comput. 269 (2019) - [j29]Peter L. Bartlett, David P. Helmbold, Philip M. Long:
Gradient Descent with Identity Initialization Efficiently Learns Positive-Definite Linear Transformations by Deep Residual Networks. Neural Comput. 31(3) (2019) - [i9]Rakshit Agrawal, Luca de Alfaro, David P. Helmbold:
A New Family of Neural Networks Provably Resistant to Adversarial Attacks. CoRR abs/1902.01208 (2019) - [i8]Yang Liu, David P. Helmbold:
Online Learning Using Only Peer Assessment. CoRR abs/1910.04382 (2019) - 2018
- [c45]Holakou Rahmanian, David P. Helmbold, S. V. N. Vishwanathan:
Online Learning of Combinatorial Objects via Extended Formulation. ALT 2018: 702-724 - [c44]Peter L. Bartlett, David P. Helmbold, Philip M. Long:
Gradient descent with identity initialization efficiently learns positive definite linear transformations. ICML 2018: 520-529 - [i7]Peter L. Bartlett, David P. Helmbold, Philip M. Long:
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks. CoRR abs/1802.06093 (2018) - 2017
- [j28]David P. Helmbold, Philip M. Long:
Surprising properties of dropout in deep networks. J. Mach. Learn. Res. 18: 200:1-200:28 (2017) - [c43]David P. Helmbold, Philip M. Long:
Surprising properties of dropout in deep networks. COLT 2017: 1123-1146 - 2016
- [c42]Atsuyoshi Nakamura
, David P. Helmbold, Manfred K. Warmuth:
Noise Free Multi-armed Bandit Game. LATA 2016: 412-423 - [i6]David P. Helmbold, Philip M. Long:
Dropout Versus Weight Decay for Deep Networks. CoRR abs/1602.04484 (2016) - [i5]Holakou Rahmanian, S. V. N. Vishwanathan, David P. Helmbold:
Extended Formulation for Online Learning of Combinatorial Objects. CoRR abs/1609.05374 (2016) - 2015
- [j27]David P. Helmbold, Philip M. Long:
On the inductive bias of dropout. J. Mach. Learn. Res. 16: 3403-3454 (2015) - 2014
- [j26]Manfred K. Warmuth, Wouter M. Koolen, David P. Helmbold:
Combining initial segments of lists. Theor. Comput. Sci. 519: 29-45 (2014) - [i4]David P. Helmbold, Philip M. Long:
On the Inductive Bias of Dropout. CoRR abs/1412.4736 (2014) - 2013
- [i3]Damian Eads, David P. Helmbold, Edward Rosten:
Boosting in Location Space. CoRR abs/1309.1080 (2013) - 2012
- [j25]David P. Helmbold, Philip M. Long:
On the necessity of irrelevant variables. J. Mach. Learn. Res. 13: 2145-2170 (2012) - [c41]James Pettit, David P. Helmbold:
Evolutionary learning of policies for MCTS simulations. FDG 2012: 212-219 - [c40]David P. Helmbold, Philip M. Long:
New Bounds for Learning Intervals with Implications for Semi-Supervised Learning. COLT 2012: 30.1-30.15 - [i2]David P. Helmbold, Philip M. Long:
On the Necessity of Irrelevant Variables. CoRR abs/1203.2557 (2012) - 2011
- [c39]Manfred K. Warmuth, Wouter M. Koolen, David P. Helmbold:
Combining Initial Segments of Lists. ALT 2011: 219-233 - [c38]David P. Helmbold, Philip M. Long:
On the Necessity of Irrelevant Variables. ICML 2011: 281-288
2000 – 2009
- 2009
- [j24]David P. Helmbold, Manfred K. Warmuth:
Learning Permutations with Exponential Weights. J. Mach. Learn. Res. 10: 1705-1736 (2009) - [c37]Damian Eads, Edward Rosten, David P. Helmbold:
Learning Object Location Predictors with Boosting and Grammar-Guided Feature Extraction. BMVC 2009: 1-11 - [c36]David P. Helmbold, Aleatha Parker-Wood:
All-Moves-As-First Heuristics in Monte-Carlo Go. IC-AI 2009: 605-610 - [i1]Damian Eads, Edward Rosten, David P. Helmbold:
Learning Object Location Predictors with Boosting and Grammar-Guided Feature Extraction. CoRR abs/0907.4354 (2009) - 2007
- [c35]Suresh K. Lodha, Darren N. Fitzpatrick, David P. Helmbold:
Aerial Lidar Data Classification using AdaBoost. 3DIM 2007: 435-442 - [c34]David P. Helmbold, Manfred K. Warmuth:
Learning Permutations with Exponential Weights. COLT 2007: 469-483 - 2006
- [j23]Graham Grindlay, David P. Helmbold:
Modeling, analyzing, and synthesizing expressive piano performance with graphical models. Mach. Learn. 65(2-3): 361-387 (2006) - [c33]Oliver Wang, Suresh K. Lodha, David P. Helmbold:
A Bayesian Approach to Building Footprint Extraction from Aerial LIDAR Data. 3DPVT 2006: 192-199 - [c32]Suresh K. Lodha, Edward J. Kreps, David P. Helmbold, Darren N. Fitzpatrick:
Aerial LiDAR Data Classification Using Support Vector Machines (SVM). 3DPVT 2006: 567-574 - 2002
- [j22]Nigel Duffy, David P. Helmbold:
Boosting Methods for Regression. Mach. Learn. 47(2-3): 153-200 (2002) - [j21]Nigel Duffy, David P. Helmbold:
A geometric approach to leveraging weak learners. Theor. Comput. Sci. 284(1): 67-108 (2002) - [j20]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) - 2001
- [j19]Claudio Gentile, David P. Helmbold:
Improved Lower Bounds for Learning from Noisy Examples: An Information-Theoretic Approach. Inf. Comput. 166(2): 133-155 (2001) - [e1]David P. Helmbold, Robert C. 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. Lecture Notes in Computer Science 2111, Springer 2001, ISBN 3-540-42343-5 [contents] - 2000
- [j18]David P. Helmbold, Nick Littlestone, Philip M. Long:
Apple Tasting. Inf. Comput. 161(2): 85-139 (2000) - [j17]David P. Helmbold, Nick Littlestone, Philip M. Long:
On-Line Learning with Linear Loss Constraints. Inf. Comput. 161(2): 140-171 (2000) - [j16]David P. Helmbold, Darrell D. E. Long, Tracey L. Sconyers, Bruce Sherrod:
Adaptive disk spin-down for mobile computers. Mob. Networks Appl. 5(4): 285-297 (2000) - [c31]Nigel Duffy, David P. Helmbold:
Leveraging for Regression. COLT 2000: 208-219
1990 – 1999
- 1999
- [j15]David P. Helmbold, Jyrki Kivinen, Manfred K. Warmuth:
Relative loss bounds for single neurons. IEEE Trans. Neural Networks 10(6): 1291-1304 (1999) - [c30]Nigel Duffy, David P. Helmbold:
A Geometric Approach to Leveraging Weak Learners. EuroCOLT 1999: 18-33 - [c29]David P. Helmbold, Sandra Panizza, Manfred K. Warmuth:
Direct and Indirect Algorithms for On-line Learning of Disjunctions. EuroCOLT 1999: 138-152 - [c28]Nigel Duffy, David P. Helmbold:
Potential Boosters? NIPS 1999: 258-264 - 1998
- [j14]Nicolò Cesa-Bianchi, David P. Helmbold, Sandra Panizza:
On Bayes Methods for On-Line Boolean Prediction. Algorithmica 22(1/2): 112-137 (1998) - [c27]Claudio Gentile, David P. Helmbold:
Improved Lower Bounds for Learning from Noisy Examples: An Information-Theoretic Approach. COLT 1998: 104-115 - 1997
- [j13]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) - [j12]David P. Helmbold, Robert E. Schapire:
Predicting Nearly As Well As the Best Pruning of a Decision Tree. Mach. Learn. 27(1): 51-68 (1997) - [j11]David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth:
A Comparison of New and Old Algorithms for a Mixture Estimation Problem. Mach. Learn. 27(1): 97-119 (1997) - [c26]David P. Helmbold, Sandra Panizza:
Some Label Efficient Learning Results. COLT 1997: 218-230 - [c25]David P. Helmbold, Stephen Kwek, Leonard Pitt:
Learning When to Trust Which Experts. EuroCOLT 1997: 134-149 - 1996
- [j10]David P. Helmbold, Charles E. McDowell:
A Taxonomy of Race Conditions. J. Parallel Distributed Comput. 33(2): 159-164 (1996) - [j9]Nicolò Cesa-Bianchi, Yoav Freund, David P. Helmbold, Manfred K. Warmuth:
On-line Prediction and Conversion Strategies. Mach. Learn. 25(1): 71-110 (1996) - [c24]Nicolò Cesa-Bianchi, David P. Helmbold, Sandra Panizza:
On Bayes Methods for On-Line Boolean Prediction. COLT 1996: 314-324 - [c23]David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth:
On-Line Portfolio Selection Using Multiplicative Updates. ICML 1996: 243-251 - [c22]David P. Helmbold, Darrell D. E. Long, Bruce Sherrod:
A Dynamic Disk Spin-Down Technique for Mobile Computing. MobiCom 1996: 130-142 - [c21]David P. Helmbold, Charles E. McDowell:
A Class of Synchronization Operations that Permit Efficient Race Detection. PDPTA 1996: 1537-1548 - 1995
- [j8]David P. Helmbold, Manfred K. Warmuth:
On Weak Learning. J. Comput. Syst. Sci. 50(3): 551-573 (1995) - [c20]David P. Helmbold, Robert E. Schapire:
Predicting Nearly as Well as the Best Pruning of a Decision Tree. COLT 1995: 61-68 - [c19]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 - [c18]David P. Helmbold, Jyrki Kivinen, Manfred K. Warmuth:
Worst-case Loss Bounds for Single Neurons. NIPS 1995: 309-315 - 1994
- [j7]David P. Helmbold, Philip M. Long:
Tracking Drifting Concepts By Minimizing Disagreements. Mach. Learn. 14(1): 27-45 (1994) - 1993
- [j6]David P. Helmbold, Charles E. McDowell, Jian-Zhong Wang:
Determining Possible Event Orders by Analyzing Sequential Traces. IEEE Trans. Parallel Distributed Syst. 4(7): 827-840 (1993) - [c17]Nicolò Cesa-Bianchi, Yoav Freund, David P. Helmbold, Manfred K. Warmuth:
On-line prediction and conversion strategies. EuroCOLT 1993: 205-216 - [c16]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 - 1992
- [j5]David P. Helmbold, Robert H. Sloan, Manfred K. Warmuth:
Learning Integer Lattices. SIAM J. Comput. 21(2): 240-266 (1992) - [c15]David P. Helmbold, Manfred K. Warmuth:
Some Weak Learning Results. COLT 1992: 399-412 - [c14]David P. Helmbold, Nick Littlestone, Philip M. Long:
Apple Tasting and Nearly One-Sided Learning. FOCS 1992: 493-502 - 1991
- [c13]David P. Helmbold, Philip M. Long:
Tracking Drifting Concepts Using Random Examples. COLT 1991: 13-23 - [c12]David P. Helmbold, Charles E. McDowell:
Computing Reachable States of Parallel Programs. Workshop on Parallel and Distributed Debugging 1991: 76-84 - 1990
- [j4]David P. Helmbold, Robert H. Sloan, Manfred K. Warmuth:
Learning Nested Differences of Intersection-Closed Concept Classes. Mach. Learn. 5: 165-196 (1990) - [j3]David P. Helmbold, Charles E. McDowell:
Modeling Speedup (n) Greater than n. IEEE Trans. Parallel Distributed Syst. 1(2): 250-256 (1990) - [c11]David P. Helmbold, Robert H. Sloan, Manfred K. Warmuth:
Learning Integer Lattices. COLT 1990: 288-302 - [c10]David P. Helmbold, Charles E. McDowell, Jian-Zhong Wang:
Analyzing Traces with Anonymous Synchronization. ICPP (2) 1990: 70-77
1980 – 1989
- 1989
- [j2]Charles E. McDowell, David P. Helmbold:
Debugging Concurrent Programs. ACM Comput. Surv. 21(4): 593-622 (1989) - [c9]David P. Helmbold, Robert H. Sloan, Manfred K. Warmuth:
Learning Nested Differences of Intersection-Closed Concept Classes. COLT 1989: 41-56 - [c8]David P. Helmbold, Charles E. McDowell:
Modeling Speedup greater than n. ICPP (3) 1989: 219-225 - 1987
- [b1]David P. Helmbold:
Parallel algorithms for scheduling and related problems. Stanford University, USA, 1987 - [j1]David P. Helmbold, Ernst W. Mayr:
Two Processor Scheduling is in NC. SIAM J. Comput. 16(4): 747-759 (1987) - [c7]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 - 1986
- [c6]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 - [c5]David P. Helmbold, Ernst W. Mayr:
Two Processor Scheduling is in NC. Aegean Workshop on Computing 1986: 12-25 - [c4]David P. Helmbold, Ernst W. Mayr:
Perfect Graphs and Parallel Algorithms. ICPP 1986: 853-860 - [c3]David P. Helmbold, Ernst W. Mayr:
Applications of Parallel Scheduling to Perfect Graphs. WG 1986: 188-203 - 1985
- [c2]David P. Helmbold, David C. Luckham:
TSL: task sequencing language. SIGAda 1985: 255-274 - 1982
- [c1]Steven M. German, David P. Helmbold, David C. Luckham:
Monitoring for deadlocks in Ada tasking. AdaTEC Conference on Ada 1982: 10-25
Coauthor Index
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