Nicolò Cesa-Bianchi

Ofer Dekel

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

From Bandits to Experts: A Tale of Domination and Independence.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Regret Minimization for Branching Experts.

[BibT_eX]

[DOI]

Proceedings of the COLT 2013, 2013

Efficient Transductive Online Learning via Randomized Rounding.

[BibT_eX]

[DOI]

Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

2012

PAC-Bayesian Inequalities for Martingales.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2012

Synergy of multi-label hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference.

[BibT_eX]

[DOI]

Matteo Re

Giorgio Valentini

Mach. Learn., 2012

PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits.

[BibT_eX]

[DOI]

Proceedings of the Workshop on On-line Trading of Exploration and Exploitation 2, 2012

Beyond Logarithmic Bounds in Online Learning.

[BibT_eX]

[DOI]

Francesco Orabona

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

A Correlation Clustering Approach to Link Classification in Signed Networks.

[BibT_eX]

[DOI]

Proceedings of the COLT 2012, 2012

Towards Minimax Policies for Online Linear Optimization with Bandit Feedback.

[BibT_eX]

[DOI]

Sébastien Bubeck

Sham M. Kakade

Proceedings of the COLT 2012, 2012

Combinatorial bandits.

[BibT_eX]

[DOI]

J. Comput. Syst. Sci., 2012

Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems.

[BibT_eX]

[DOI]

Sébastien Bubeck

Found. Trends Mach. Learn., 2012

Memory Constraint Online Multitask Classification

[BibT_eX]

[DOI]

CoRR, 2012

A new look at shifting regret

[BibT_eX]

[DOI]

CoRR, 2012

A Linear Time Active Learning Algorithm for Link Classification.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Mirror Descent Meets Fixed Share (and feels no regret).

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011

Online Learning of Noisy Data.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2011

Predicting the labels of an unknown graph via adaptive exploration.

[BibT_eX]

[DOI]

Fabio Vitale

Theor. Comput. Sci., 2011

Learning noisy linear classifiers via adaptive and selective sampling.

[BibT_eX]

[DOI]

Mach. Learn., 2011

Efficient Learning with Partially Observed Attributes.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2011

PAC-Bayesian Analysis of the Exploration-Exploitation Trade-off

[BibT_eX]

[DOI]

CoRR, 2011

See the Tree Through the Lines: The Shazoo Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Efficient Online Learning via Randomized Rounding.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Ensembles and Multiple Classifiers: A Game-Theoretic View.

[BibT_eX]

[DOI]

Proceedings of the Multiple Classifier Systems - 10th International Workshop, 2011

Better Algorithms for Selective Sampling.

[BibT_eX]

[DOI]

Francesco Orabona

Proceedings of the 28th International Conference on Machine Learning, 2011

The Game-Theoretic Approach to Machine Learning and Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Adaptive and Intelligent Systems - Second International Conference, 2011

Quantity Makes Quality: Learning with Partial Views.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010

Guest Editorial: Learning from multiple sources.

[BibT_eX]

[DOI]

David R. Hardoon

Gayle Leen

Mach. Learn., 2010

Hierarchical Cost-Sensitive Algorithms for Genome-Wide Gene Function Prediction.

[BibT_eX]

[DOI]

Giorgio Valentini

Proceedings of the third International Workshop on Machine Learning in Systems Biology, 2010

Linear Algorithms for Online Multitask Classification.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2010

Random Spanning Trees and the Prediction of Weighted Graphs.

[BibT_eX]

[DOI]

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

OM-2: An online multi-class Multi-Kernel Learning algorithm Luo Jie.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2010

Online Learning of Noisy Data with Kernels.

[BibT_eX]

[DOI]

Proceedings of the COLT 2010, 2010

Active Learning on Trees and Graphs.

[BibT_eX]

[DOI]

Proceedings of the COLT 2010, 2010

2009

Robust bounds for classification via selective sampling.

[BibT_eX]

[DOI]

Francesco Orabona

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Online learning for CAT applications.

[BibT_eX]

[DOI]

Gabriele Reverberi

Proceedings of the Workshop on Statistical Multilingual Analysis for Retrieval and Translation, 2009

Fast and Optimal Prediction on a Labeled Tree.

[BibT_eX]

[DOI]

Fabio Vitale

Proceedings of the COLT 2009, 2009

Online discriminative learning: theory and applications.

[BibT_eX]

[DOI]

Proceedings of the 2009 IEEE Workshop on Automatic Speech Recognition & Understanding, 2009

Learning Unknown Graphs.

[BibT_eX]

[DOI]

Fabio Vitale

Proceedings of the Algorithmic Learning Theory, 20th International Conference, 2009

2008

Improved Risk Tail Bounds for On-Line Algorithms.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2008

HCGene: a software tool to support the hierarchical classification of genes.

[BibT_eX]

[DOI]

Giorgio Valentini

Bioinform., 2008

Linear Classification and Selective Sampling Under Low Noise Conditions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007

Applications of regularized least squares to pattern classification.

[BibT_eX]

[DOI]

Theor. Comput. Sci., 2007

Improved second-order bounds for prediction with expert advice.

[BibT_eX]

[DOI]

Yishay Mansour

Gilles Stoltz

Mach. Learn., 2007

Tracking the best hyperplane with a simple budget Perceptron.

[BibT_eX]

[DOI]

Mach. Learn., 2007

2006

Foreword.

[BibT_eX]

[DOI]

Rüdiger Reischuk

Thomas Zeugmann

Theor. Comput. Sci., 2006

Regret Minimization Under Partial Monitoring.

[BibT_eX]

[DOI]

Gilles Stoltz

Math. Oper. Res., 2006

Worst-Case Analysis of Selective Sampling for Linear Classification.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2006

Incremental Algorithms for Hierarchical Classification.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2006

A distributed voting scheme to maximize preferences.

[BibT_eX]

[DOI]

RAIRO Theor. Informatics Appl., 2006

Hierarchical classification: combining Bayes with SVM.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2006

Tracking the Best Hyperplane with a Simple Budget Perceptron.

[BibT_eX]

[DOI]

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

Prediction, learning, and games.

[BibT_eX]

[DOI]

Cambridge University Press, ISBN: 978-0-511-54692-1, 2006

2005

Minimizing regret with label efficient prediction.

[BibT_eX]

[DOI]

Gilles Stoltz

IEEE Trans. Inf. Theory, 2005

A Second-Order Perceptron Algorithm.

[BibT_eX]

[DOI]

SIAM J. Comput., 2005

A Distributed Architecture for Management and Retrieval of Extended Points of Interest.

[BibT_eX]

[DOI]

Claudio Bettini

Daniele Riboni

Proceedings of the 25th International Conference on Distributed Computing Systems Workshops (ICDCS 2005 Workshops), 2005

2004

On the Generalization Ability of On-Line Learning Algorithms.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2004

Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Incremental Algorithms for Hierarchical Classification.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Towards Highly Adaptive Services for Mobile Computing.

[BibT_eX]

Proceedings of the Mobile Information Systems, 2004

Regret Bounds for Hierarchical Classification with Linear-Threshold Functions.

[BibT_eX]

[DOI]

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

Applications of Regularized Least Squares to Classification Problems.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004

2003

Potential-Based Algorithms in On-Line Prediction and Game Theory.

[BibT_eX]

[DOI]

Mach. Learn., 2003

Learning Probabilistic Linear-Threshold Classifiers via Selective Sampling.

[BibT_eX]

[DOI]

Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002

The Nonstochastic Multiarmed Bandit Problem.

[BibT_eX]

[DOI]

SIAM J. Comput., 2002

Finite-time Analysis of the Multiarmed Bandit Problem.

[BibT_eX]

[DOI]

Paul Fischer

Mach. Learn., 2002

Adaptive and Self-Confident On-Line Learning Algorithms.

[BibT_eX]

[DOI]

J. Comput. Syst. Sci., 2002

Kernel Methods for Document Filtering.

[BibT_eX]

[DOI]

Proceedings of The Eleventh Text REtrieval Conference, 2002

Margin-Based Algorithms for Information Filtering.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Editors' Introduction.

[BibT_eX]

[DOI]

Masayuki Numao

Rüdiger Reischuk

Proceedings of the Algorithmic Learning Theory, 13th International Conference, 2002

2001

Worst-Case Bounds for the Logarithmic Loss of Predictors.

[BibT_eX]

[DOI]

Mach. Learn., 2001

Potential-Based Algorithms in Online Prediction and Game Theory.

[BibT_eX]

[DOI]

Proceedings of the Computational Learning Theory, 2001

2000

On-line Learning with Malicious Noise and the Closure Algorithm

[BibT_eX]

[DOI]

Electron. Colloquium Comput. Complex., 2000

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

[BibT_eX]

[DOI]

Electron. Colloquium Comput. Complex., 2000

1999

Guest Editors' Introduction.

[BibT_eX]

[DOI]

Jonathan Baxter

Mach. Learn., 1999

Analysis of Two Gradient-Based Algorithms for On-Line Regression.

[BibT_eX]

[DOI]

J. Comput. Syst. Sci., 1999

Sample-Efficient Strategies for Learning in the Presence of Noise.

[BibT_eX]

[DOI]

J. ACM, 1999

Minimax Regret Under log Loss for General Classes of Experts.

[BibT_eX]

[DOI]

Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 1999

1998

A Graph-theoretic Generalization of the Sauer-Shelah Lemma.

[BibT_eX]

[DOI]

David Haussler

Discret. Appl. Math., 1998

On Bayes Methods for On-Line Boolean Prediction.

[BibT_eX]

[DOI]

David P. Helmbold

Sandra Panizza

Algorithmica, 1998

Finite-Time Regret Bounds for the Multiarmed Bandit Problem.

[BibT_eX]

Paul Fischer

Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

On Sequential Prediction of Individual Sequences Relative to a Set of Experts.

[BibT_eX]

[DOI]

Proceedings of the Eleventh Annual Conference on Computational Learning Theory, 1998

1997

How to use expert advice.

[BibT_eX]

[DOI]

J. ACM, 1997

Scale-sensitive dimensions, uniform convergence, and learnability.

[BibT_eX]

[DOI]

J. ACM, 1997

Randomized Hypotheses and Minimum Disagreement Hypotheses for Learning with Noise.

[BibT_eX]

[DOI]

Proceedings of the Computational Learning Theory, Third European Conference, 1997

1996

Worst-case quadratic loss bounds for prediction using linear functions and gradient descent.

[BibT_eX]

[DOI]

Philip M. Long

Manfred K. Warmuth

IEEE Trans. Neural Networks, 1996

On-line Prediction and Conversion Strategies.

[BibT_eX]

[DOI]

Mach. Learn., 1996

Noise-Tolerant Learning Near the Information-Theoretic Bound.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth Annual ACM Symposium on the Theory of Computing, 1996

Tight Bounds on the Cumulative Profit of Distributed Voters (Abstract).

[BibT_eX]

[DOI]

Pasquale Caianiello

Proceedings of the Fifteenth Annual ACM Symposium on Principles of Distributed Computing, 1996

1995

Characterizations of Learnability for Classes of {0, ..., n}-Valued Functions.

[BibT_eX]

[DOI]

J. Comput. Syst. Sci., 1995

Efficient Learning with Equivalence Queries of Conjunctions of Modulo Functions.

[BibT_eX]

[DOI]

Alberto Bertoni

Guido Fiorino

Inf. Process. Lett., 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

Bounds on approximate steepest descent for likelihood maximization in exponential families.

[BibT_eX]

[DOI]

Anders Krogh

Manfred K. Warmuth

IEEE Trans. Inf. Theory, 1994

1993

Worst-Case Quadratic Loss Bounds for a Generalization of the Widrow-Hoff Rule.

[BibT_eX]

[DOI]

Philip M. Long

Manfred K. Warmuth

Proceedings of the Sixth Annual ACM Conference on Computational Learning Theory, 1993

1992

Characterizations of Learnability for Classes of {<i>O, ..., n</i>}-Valued Functions.

[BibT_eX]

[DOI]

Shai Ben-David

Philip M. Long

Proceedings of the Fifth Annual ACM Conference on Computational Learning Theory, 1992

1990

Learning the Distribution in the Extended PAC Model.

[BibT_eX]

Proceedings of the Algorithmic Learning Theory, First International Workshop, 1990

1988

Microcanonical annealing on neural networks.

[BibT_eX]

[DOI]

Gianpiero Cattaneo