Robert E. Schapire

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

The Convergence Rate of AdaBoost.

[BibT_eX]

[DOI]

Proceedings of the COLT 2010, 2010

2009

Speed and Sparsity of Regularized Boosting.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Margin-based Ranking and an Equivalence between AdaBoost and RankBoost.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2009

Aneuploidy prediction and tumor classification with heterogeneous hidden conditional random fields.

[BibT_eX]

[DOI]

Bioinform., 2009

2008

On reoptimizing multi-class classifiers.

[BibT_eX]

[DOI]

Mach. Learn., 2008

From Optimization to Regret Minimization and Back Again.

[BibT_eX]

[DOI]

Ioannis C. Avramopoulos

Jennifer Rexford

Proceedings of the Third Workshop on Tackling Computer Systems Problems with Machine Learning Techniques, 2008

Apprenticeship learning using linear programming.

[BibT_eX]

[DOI]

Umar Syed

Michael H. Bowling

Proceedings of the Machine Learning, 2008

2007

Maximum Entropy Correlated Equilibria.

[BibT_eX]

[DOI]

Luis E. Ortiz

Sham M. Kakade

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Maximum Entropy Density Estimation with Generalized Regularization and an Application to Species Distribution Modeling.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2007

Imitation Learning with a Value-Based Prior.

[BibT_eX]

[DOI]

Umar Syed

Proceedings of the UAI 2007, 2007

A Game-Theoretic Approach to Apprenticeship Learning.

[BibT_eX]

[DOI]

Umar Syed

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

FilterBoost: Regression and Classification on Large Datasets.

[BibT_eX]

[DOI]

Joseph K. Bradley

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Hierarchical maximum entropy density estimation.

[BibT_eX]

[DOI]

David M. Blei

Proceedings of the Machine Learning, 2007

2006

Hierarchical multi-label prediction of gene function.

[BibT_eX]

[DOI]

Zafer Barutçuoglu

Olga G. Troyanskaya

Bioinform., 2006

How boosting the margin can also boost classifier complexity.

[BibT_eX]

[DOI]

Lev Reyzin

Proceedings of the Machine Learning, 2006

Algorithms for portfolio management based on the Newton method.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2006

Maximum Entropy Distribution Estimation with Generalized Regularization.

[BibT_eX]

[DOI]

Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

2005

Boosting with prior knowledge for call classification.

[BibT_eX]

[DOI]

IEEE Trans. Speech Audio Process., 2005

Combining active and semi-supervised learning for spoken language understanding.

[BibT_eX]

[DOI]

Gökhan Tür

Dilek Hakkani-Tür

Speech Commun., 2005

Efficient Multiclass Implementations of L1-Regularized Maximum Entropy

[BibT_eX]

[DOI]

Patrick Haffner

CoRR, 2005

Convergence and Consistency of Regularized Boosting Algorithms with Stationary B-Mixing Observations.

[BibT_eX]

[DOI]

Aurélie C. Lozano

Sanjeev R. Kulkarni

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Correcting sample selection bias in maximum entropy density estimation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Margin-Based Ranking Meets Boosting in the Middle.

[BibT_eX]

[DOI]

Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

2004

The Dynamics of AdaBoost: Cyclic Behavior and Convergence of Margins.

[BibT_eX]

[DOI]

Ingrid Daubechies

J. Mach. Learn. Res., 2004

A maximum entropy approach to species distribution modeling.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2004

Boosting Based on a Smooth Margin.

[BibT_eX]

[DOI]

Ingrid Daubechies

Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

Performance Guarantees for Regularized Maximum Entropy Density Estimation.

[BibT_eX]

[DOI]

Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

2003

An Efficient Boosting Algorithm for Combining Preferences.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2003

Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2003

On the Dynamics of Boosting.

[BibT_eX]

[DOI]

Ingrid Daubechies

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Active learning for spoken language understanding.

[BibT_eX]

[DOI]

Gökhan Tür

Dilek Hakkani-Tür

Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

2002

The Nonstochastic Multiarmed Bandit Problem.

[BibT_eX]

[DOI]

SIAM J. Comput., 2002

Logistic Regression, AdaBoost and Bregman Distances.

[BibT_eX]

[DOI]

Michael Collins

Mach. Learn., 2002

Advances in Boosting.

[BibT_eX]

[DOI]

Proceedings of the UAI '02, 2002

AT&t help desk.

[BibT_eX]

[DOI]

Giuseppe Di Fabbrizio

Proceedings of the 7th International Conference on Spoken Language Processing, ICSLP2002, 2002

Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation.

[BibT_eX]

Proceedings of the Machine Learning, 2002

Incorporating Prior Knowledge into Boosting.

[BibT_eX]

Proceedings of the Machine Learning, 2002

Combining prior knowledge and boosting for call classification in spoken language dialogue.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2002

ATTac-2001: A Learning, Autonomous Bidding Agent.

[BibT_eX]

[DOI]

Proceedings of the Agent-Mediated Electronic Commerce IV, 2002

2001

Drifting Games.

[BibT_eX]

[DOI]

Mach. Learn., 2001

A Generalization of Principal Components Analysis to the Exponential Family.

[BibT_eX]

[DOI]

Michael Collins

Sanjoy Dasgupta

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Why averaging classifiers can protect against overfitting.

[BibT_eX]

[DOI]

Yishay Mansour

Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000

BoosTexter: A Boosting-based System for Text Categorization.

[BibT_eX]

[DOI]

Mach. Learn., 2000

Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers.

[BibT_eX]

[DOI]

Erin L. Allwein

J. Mach. Learn. Res., 2000

Gambling in a rigged casino: The adversarial multi-armed bandit problem

[BibT_eX]

[DOI]

Electron. Colloquium Comput. Complex., 2000

On the Convergence Rate of Good-Turing Estimators.

[BibT_eX]

David A. McAllester

Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

Boosting for Document Routing.

[BibT_eX]

[DOI]

Proceedings of the 2000 ACM CIKM International Conference on Information and Knowledge Management, 2000

1999

Improved Boosting Algorithms Using Confidence-rated Predictions.

[BibT_eX]

[DOI]

Mach. Learn., 1999

Large Margin Classification Using the Perceptron Algorithm.

[BibT_eX]

[DOI]

Mach. Learn., 1999

Learning to Order Things.

[BibT_eX]

[DOI]

William W. Cohen

J. Artif. Intell. Res., 1999

A Brief Introduction to Boosting.

[BibT_eX]

[DOI]

Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 1999

Theoretical Views of Boosting.

[BibT_eX]

[DOI]

Proceedings of the Computational Learning Theory, 4th European Conference, 1999

Boosting Applied to Tagging and PP Attachment.

[BibT_eX]

[DOI]

Steven Abney

Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora, 1999

Theoretical Views of Boosting and Applications.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 10th International Conference, 1999

1998

Boosting and Rocchio Applied to Text Filtering.

[BibT_eX]

[DOI]

Amit Singhal

Proceedings of the SIGIR '98: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 1998

1997

A Comparison of New and Old Algorithms for a Mixture Estimation Problem.

[BibT_eX]

[DOI]

Mach. Learn., 1997

Predicting Nearly As Well As the Best Pruning of a Decision Tree.

[BibT_eX]

[DOI]

David P. Helmbold

Mach. Learn., 1997

A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting.

[BibT_eX]

[DOI]

J. Comput. Syst. Sci., 1997

How to use expert advice.

[BibT_eX]

[DOI]

J. ACM, 1997

Efficient Learning of Typical Finite Automata from Random Walks.

[BibT_eX]

[DOI]

Inf. Comput., 1997

Using and Combining Predictors That Specialize.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth Annual ACM Symposium on the Theory of Computing, 1997

Boosting the margin: A new explanation for the effectiveness of voting methods.

[BibT_eX]

Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

Using output codes to boost multiclass learning problems.

[BibT_eX]

Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

1996

On the Worst-Case Analysis of Temporal-Difference Learning Algorithms.

[BibT_eX]

[DOI]

Manfred K. Warmuth

Mach. Learn., 1996

Learning Sparse Multivariate Polynomials over a Field with Queries and Counterexamples.

[BibT_eX]

[DOI]

Linda Sellie

J. Comput. Syst. Sci., 1996

Training Algorithms for Linear Text Classifiers.

[BibT_eX]

[DOI]

Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 1996

On-Line Portfolio Selection Using Multiplicative Updates.

[BibT_eX]

Proceedings of the Machine Learning, 1996

Experiments with a New Boosting Algorithm.

[BibT_eX]

Proceedings of the Machine Learning, 1996

Game Theory, On-Line Prediction and Boosting.

[BibT_eX]

[DOI]

Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

1995

On the Sample Complexity of Weakly Learning

[BibT_eX]

[DOI]

Inf. Comput., March, 1995

Efficient Algorithms for Learning to Play Repeated Games Against Computationally Bounded Adversaries.

[BibT_eX]

[DOI]

Proceedings of the 36th Annual Symposium on Foundations of Computer Science, 1995

Gambling in a Rigged Casino: The Adversarial Multi-Arm Bandit Problem.

[BibT_eX]

[DOI]

Proceedings of the 36th Annual Symposium on Foundations of Computer Science, 1995

1994

Learning Probabilistic Read-once Formulas on Product Distributions.

[BibT_eX]

[DOI]

Mach. Learn., 1994

Toward Efficient Agnostic Learning.

[BibT_eX]

[DOI]

Linda Sellie

Mach. Learn., 1994

Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension.

[BibT_eX]

[DOI]

David Haussler

Mach. Learn., 1994

Efficient Distribution-Free Learning of Probabilistic Concepts.

[BibT_eX]

[DOI]

J. Comput. Syst. Sci., 1994

Diversity-Based Inference of Finite Automata.

[BibT_eX]

[DOI]

J. ACM, 1994

On the learnability of discrete distributions.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Sixth Annual ACM Symposium on Theory of Computing, 1994

1993

Inference of Finite Automata Using Homing Sequences

[BibT_eX]

[DOI]

Inf. Comput., April, 1993

Learning Binary Relations and Total Orders.

[BibT_eX]

[DOI]

SIAM J. Comput., 1993

Exact Identification of Read-Once Formulas Using Fixed Points of Amplification Functions.

[BibT_eX]

[DOI]

SIAM J. Comput., 1993

Boosting Performance in Neural Networks.

[BibT_eX]

[DOI]

Harris Drucker

Patrice Y. Simard

Int. J. Pattern Recognit. Artif. Intell., 1993

1992

Improving Performance in Neural Networks Using a Boosting Algorithm.

[BibT_eX]

[DOI]

Harris Drucker

Patrice Y. Simard

Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

Design and analysis of efficient learning algorithms.

[BibT_eX]

ACM Doctoral dissertation award ; 1991, MIT Press, ISBN: 978-0-262-19325-2, 1992

1991

Estimating Average-Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 4, 1991

1990

The Strength of Weak Learnability.

[BibT_eX]

[DOI]

Mach. Learn., 1990

Efficient Distribution-free Learning of Probabilistic Concepts (Extended Abstract)

[BibT_eX]

[DOI]

Proceedings of the 31st Annual Symposium on Foundations of Computer Science, 1990

Exact Identification of Circuits Using Fixed Points of Amplification Functions (Extended Abstract)

[BibT_eX]

[DOI]

Proceedings of the 31st Annual Symposium on Foundations of Computer Science, 1990

Pattern Languages are not Learnable.

[BibT_eX]

[DOI]

Proceedings of the Third Annual Workshop on Computational Learning Theory, 1990

Efficient Distribution-Free Learning of Probabilistic Concepts (Abstract).

[BibT_eX]

[DOI]

Proceedings of the Third Annual Workshop on Computational Learning Theory, 1990

Exact Identification of Circuits Using Fixed Points of Amplification Functions (Abstract).

[BibT_eX]

[DOI]

Proceedings of the Third Annual Workshop on Computational Learning Theory, 1990

On the Sample Complexity of Weak Learning.

[BibT_eX]

[DOI]

Proceedings of the Third Annual Workshop on Computational Learning Theory, 1990

1989

Inference of Finite Automata Using Homing Sequences (Extended Abstract)

[BibT_eX]

[DOI]

Proceedings of the 21st Annual ACM Symposium on Theory of Computing, 1989

The Strength of Weak Learnability (Extended Abstract)

[BibT_eX]

[DOI]

Proceedings of the 30th Annual Symposium on Foundations of Computer Science, Research Triangle Park, North Carolina, USA, 30 October, 1989

Learning Binary Relations and Total Orders (Extended Abstract)

[BibT_eX]

[DOI]

Proceedings of the 30th Annual Symposium on Foundations of Computer Science, Research Triangle Park, North Carolina, USA, 30 October, 1989

1987

Diversity-Based Inference of Finite Automata (Extended Abstract)

[BibT_eX]

[DOI]