Monitoring for deadlocks in Ada tasking. - Steven M. German; David P. Helmbold; David C. Luckham (AdaTEC Conference on Ada, 1982)

TSL: task sequencing language. - David P. Helmbold; David C. Luckham (SIGAda, 1985)

Task Sequencing Languages for Specifying Distributed Ada Systems. - David C. Luckham; David P. Helmbold; Sigurd Meldal; D. L. Bryan; M. A. Haberler (System Development and Ada, 1986)

Perfect Graphs and Parallel Algorithms. - David P. Helmbold; Ernst W. Mayr (ICPP, 1986)

Applications of Parallel Scheduling to Perfect Graphs. - David P. Helmbold; Ernst W. Mayr (WG, 1986)

Task Sequencing Language for Specifying Distributed Ada Systems. - David C. Luckham; David P. Helmbold; D. L. Bryan; M. A. Haberler (PARLE (2), 1987)

Two Processor Scheduling is in NC. - David P. Helmbold; Ernst W. Mayr (SIAM J. Comput., 1987)

Parallel algorithms for scheduling and related problems. - David P. Helmbold (1987)

Modeling Speedup greater than n. - David P. Helmbold; Charles E. McDowell (ICPP (3), 1989)

Debugging Concurrent Programs. - Charles E. McDowell; David P. Helmbold (ACM Comput. Surv., 1989)

Analyzing Traces with Anonymous Synchronization. - David P. Helmbold; Charles E. McDowell; Jian-Zhong Wang (ICPP (2), 1990)

Learning Nested Differences of Intersection-Closed Concept Classes. - David P. Helmbold; Robert Sloan 001; Manfred K. Warmuth (Mach. Learn., 1990)

Modeling Speedup (n) Greater than n. - David P. Helmbold; Charles E. McDowell (IEEE Trans. Parallel Distributed Syst., 1990)

Tracking Drifting Concepts Using Random Examples. - David P. Helmbold; Philip M. Long (COLT, 1991)

Computing Reachable States of Parallel Programs. - David P. Helmbold; Charles E. McDowell (Workshop on Parallel and Distributed Debugging, 1991)

Some Weak Learning Results. - David P. Helmbold; Manfred K. Warmuth (COLT, 1992)

Apple Tasting and Nearly One-Sided Learning - David P. Helmbold; Nick Littlestone; Philip M. Long (FOCS, 1992)

Learning Integer Lattices. - David P. Helmbold; Robert Sloan 001; Manfred K. Warmuth (SIAM J. Comput., 1992)

Determining Possible Event Orders by Analyzing Sequential Traces. - David P. Helmbold; Charles E. McDowell; Jian-Zhong Wang (IEEE Trans. Parallel Distributed Syst., 1993)

Tracking Drifting Concepts By Minimizing Disagreements. - David P. Helmbold; Philip M. Long (Mach. Learn., 1994)

Worst-case Loss Bounds for Single Neurons. - David P. Helmbold; Jyrki Kivinen; Manfred K. Warmuth (NIPS, 1995)

On Weak Learning. - David P. Helmbold; Manfred K. Warmuth (J. Comput. Syst. Sci., 1995)

On-Line Portfolio Selection Using Multiplicative Updates. - David P. Helmbold; Robert E. Schapire; Yoram Singer; Manfred K. Warmuth (ICML, 1996)

A Dynamic Disk Spin-Down Technique for Mobile Computing. - David P. Helmbold; Darrell D. E. Long; Bruce Sherrod (MobiCom, 1996)

A Class of Synchronization Operations that Permit Efficient Race Detection. - David P. Helmbold; Charles E. McDowell (PDPTA, 1996)

A Taxonomy of Race Conditions. - David P. Helmbold; Charles E. McDowell (J. Parallel Distributed Comput., 1996)

On-line Prediction and Conversion Strategies. - Nicolò Cesa-Bianchi; Yoav Freund; David P. Helmbold; Manfred K. Warmuth (Mach. Learn., 1996)

Some Label Efficient Learning Results. - David P. Helmbold; Sandra Panizza (COLT, 1997)

Learning When to Trust Which Experts. - David P. Helmbold; Stephen Kwek; Leonard Pitt (EuroCOLT, 1997)

How to use expert advice. - Nicolò Cesa-Bianchi; Yoav Freund; David Haussler; David P. Helmbold; Robert E. Schapire; Manfred K. Warmuth (J. ACM, 1997)

Predicting Nearly As Well As the Best Pruning of a Decision Tree. - David P. Helmbold; Robert E. Schapire (Mach. Learn., 1997)

A Comparison of New and Old Algorithms for a Mixture Estimation Problem. - David P. Helmbold; Robert E. Schapire; Yoram Singer; Manfred K. Warmuth (Mach. Learn., 1997)

On Bayes Methods for On-Line Boolean Prediction. - Nicolò Cesa-Bianchi; David P. Helmbold; Sandra Panizza (Algorithmica, 1998)

Potential Boosters? - Nigel Duffy; David P. Helmbold (NIPS, 1999)

Relative loss bounds for single neurons. - David P. Helmbold; Jyrki Kivinen; Manfred K. Warmuth (IEEE Trans. Neural Networks, 1999)

Leveraging for Regression. - Nigel Duffy; David P. Helmbold (COLT, 2000)

Apple Tasting. - David P. Helmbold; Nick Littlestone; Philip M. Long (Inf. Comput., 2000)

On-Line Learning with Linear Loss Constraints. - David P. Helmbold; Nick Littlestone; Philip M. Long (Inf. Comput., 2000)

Adaptive disk spin-down for mobile computers. - David P. Helmbold; Darrell D. E. Long; Tracey L. Sconyers; Bruce Sherrod (Mob. Networks Appl., 2000)

Improved Lower Bounds for Learning from Noisy Examples: An Information-Theoretic Approach. - Claudio Gentile; David P. Helmbold (Inf. Comput., 2001)

Boosting Methods for Regression. - Nigel Duffy; David P. Helmbold (Mach. Learn., 2002)

A geometric approach to leveraging weak learners. - Nigel Duffy; David P. Helmbold (Theor. Comput. Sci., 2002)

Direct and indirect algorithms for on-line learning of disjunctions. - David P. Helmbold; Sandra Panizza; Manfred K. Warmuth (Theor. Comput. Sci., 2002)

Aerial LiDAR Data Classification Using Support Vector Machines (SVM). - Suresh K. Lodha; Edward J. Kreps; David P. Helmbold; Darren N. Fitzpatrick (3DPVT, 2006)

A Bayesian Approach to Building Footprint Extraction from Aerial LIDAR Data. - Oliver Wang; Suresh K. Lodha; David P. Helmbold (3DPVT, 2006)

Modeling, analyzing, and synthesizing expressive piano performance with graphical models. - Graham Grindlay; David P. Helmbold (Mach. Learn., 2006)

Aerial Lidar Data Classification using AdaBoost. - Suresh K. Lodha; Darren N. Fitzpatrick; David P. Helmbold (3DIM, 2007)

Learning Object Location Predictors with Boosting and Grammar-Guided Feature Extraction. - Damian Eads; Edward Rosten; David P. Helmbold (BMVC, 2009)

All-Moves-As-First Heuristics in Monte-Carlo Go. - David P. Helmbold; Aleatha Parker-Wood (IC-AI, 2009)

Learning Permutations with Exponential Weights. - David P. Helmbold; Manfred K. Warmuth (J. Mach. Learn. Res., 2009)

Evolutionary learning of policies for MCTS simulations. - James Pettit; David P. Helmbold (FDG, 2012)

New Bounds for Learning Intervals with Implications for Semi-Supervised Learning. - David P. Helmbold; Philip M. Long (COLT, 2012)

On the necessity of irrelevant variables. - David P. Helmbold; Philip M. Long (J. Mach. Learn. Res., 2012)

Boosting in Location Space. - Damian Eads; David P. Helmbold; Edward Rosten (CoRR, 2013)

Combining initial segments of lists. - Manfred K. Warmuth; Wouter M. Koolen; David P. Helmbold (Theor. Comput. Sci., 2014)

On the inductive bias of dropout. - David P. Helmbold; Philip M. Long (J. Mach. Learn. Res., 2015)

Noise Free Multi-armed Bandit Game. - Atsuyoshi Nakamura; David P. Helmbold; Manfred K. Warmuth (LATA, 2016)

Dropout Versus Weight Decay for Deep Networks. - David P. Helmbold; Philip M. Long (CoRR, 2016)

Extended Formulation for Online Learning of Combinatorial Objects. - Holakou Rahmanian; S. V. N. Vishwanathan; David P. Helmbold (CoRR, 2016)

Surprising properties of dropout in deep networks. - David P. Helmbold; Philip M. Long (J. Mach. Learn. Res., 2017)

Online Learning of Combinatorial Objects via Extended Formulation. - Holakou Rahmanian; David P. Helmbold; S. V. N. Vishwanathan (ALT, 2018)

Gradient descent with identity initialization efficiently learns positive definite linear transformations. - Peter L. Bartlett; David P. Helmbold; Philip M. Long (ICML, 2018)

A New Family of Neural Networks Provably Resistant to Adversarial Attacks. - Rakshit Agrawal; Luca de Alfaro; David P. Helmbold (CoRR, 2019)

Online Learning Using Only Peer Assessment. - Yang Liu 018; David P. Helmbold (CoRR, 2019)

Mistake bounds on the noise-free multi-armed bandit game. - Atsuyoshi Nakamura; David P. Helmbold; Manfred K. Warmuth (Inf. Comput., 2019)

Gradient Descent with Identity Initialization Efficiently Learns Positive-Definite Linear Transformations by Deep Residual Networks. - Peter L. Bartlett; David P. Helmbold; Philip M. Long (Neural Comput., 2019)

Online Learning Using Only Peer Prediction. - Yang Liu 018; David P. Helmbold (AISTATS, 2020)