Gábor Lugosi

According to our database1, Gábor Lugosi authored at least 114 papers between 1992 and 2019.

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Bibliography

2019
Online Influence Maximization with Local Observations.
Proceedings of the Algorithmic Learning Theory, 2019

2018
Multiplayer bandits without observing collision information.
CoRR, 2018

Online Influence Maximization with Local Observations.
CoRR, 2018

2017
Finding Adam in random growing trees.
Random Struct. Algorithms, 2017

On the measure of Voronoi cells.
J. Applied Probability, 2017

Local optima of the Sherrington-Kirkpatrick Hamiltonian.
CoRR, 2017

On the Hardness of Inventory Management with Censored Demand Data.
CoRR, 2017

An Improved Parametrization and Analysis of the EXP3++ Algorithm for Stochastic and Adversarial Bandits.
CoRR, 2017

Algorithmic stability and hypothesis complexity.
CoRR, 2017

Boltzmann Exploration Done Right.
CoRR, 2017

Boltzmann Exploration Done Right.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Algorithmic Stability and Hypothesis Complexity.
Proceedings of the 34th International Conference on Machine Learning, 2017

An Improved Parametrization and Analysis of the EXP3++ Algorithm for Stochastic and Adversarial Bandits.
Proceedings of the 30th Conference on Learning Theory, 2017

2015
Random-Walk Perturbations for Online Combinatorial Optimization.
IEEE Trans. Information Theory, 2015

Exceptional rotations of random graphs: a VC theory.
Journal of Machine Learning Research, 2015

Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 15361).
Dagstuhl Reports, 2015

2014
Detection of Correlations With Adaptive Sensing.
IEEE Trans. Information Theory, 2014

Connectivity threshold of Bluetooth graphs.
Random Struct. Algorithms, 2014

Regret in Online Combinatorial Optimization.
Math. Oper. Res., 2014

Finding Adam in random growing trees.
CoRR, 2014

Almost optimal sparsification of random geometric graphs.
CoRR, 2014

Connectivity of sparse Bluetooth networks.
CoRR, 2014

Density-preserving quantization with application to graph downsampling.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Bandits With Heavy Tail.
IEEE Trans. Information Theory, 2013

Prediction by Random-Walk Perturbation
CoRR, 2013

Prediction by random-walk perturbation.
Proceedings of the COLT 2013, 2013

2012
Efficient Tracking of Large Classes of Experts.
IEEE Trans. Information Theory, 2012

Combinatorial bandits.
J. Comput. Syst. Sci., 2012

Bandits with heavy tail
CoRR, 2012

Regret in Online Combinatorial Optimization
CoRR, 2012

A new look at shifting regret
CoRR, 2012

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

Efficient tracking of large classes of experts.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

2011
Preface.
Theor. Comput. Sci., 2011

Minimax Policies for Combinatorial Prediction Games.
Proceedings of the COLT 2011, 2011

Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 11291).
Dagstuhl Reports, 2011

Efficient Tracking of Large Classes of Experts
CoRR, 2011

Connectivity threshold for Bluetooth graphs
CoRR, 2011

2010
On-Line Sequential Bin Packing.
Journal of Machine Learning Research, 2010

The Longest Minimum-Weight Path in a Complete Graph.
Combinatorics, Probability & Computing, 2010

2009
Multiple choice tries and distributed hash tables.
Random Struct. Algorithms, 2009

Online Multi-task Learning with Hard Constraints
CoRR, 2009

Online Multi-task Learning with Hard Constraints.
Proceedings of the COLT 2009, 2009

Combinatorial Bandits.
Proceedings of the COLT 2009, 2009

2008
Tracking the Best Quantizer.
IEEE Trans. Information Theory, 2008

On the Performance of Clustering in Hilbert Spaces.
IEEE Trans. Information Theory, 2008

Strategies for Prediction Under Imperfect Monitoring.
Math. Oper. Res., 2008

Consistency of Random Forests and Other Averaging Classifiers.
Journal of Machine Learning Research, 2008

A simple randomized algorithm for sequential prediction of ergodic time series.
CoRR, 2008

Concentration Inequalities.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

On-line Sequential Bin Packing.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007
Introduction to the special issue on COLT 2006.
Machine Learning, 2007

The On-Line Shortest Path Problem Under Partial Monitoring.
Journal of Machine Learning Research, 2007

Learning correlated equilibria in games with compact sets of strategies.
Games and Economic Behavior, 2007

Global Nash convergence of Foster and Young's regret testing.
Games and Economic Behavior, 2007

Strategies for prediction under imperfect monitoring
CoRR, 2007

The on-line shortest path problem under partial monitoring
CoRR, 2007

Multiple choice tries and distributed hash tables.
Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2007

Strategies for Prediction Under Imperfect Monitoring.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

Sequential prediction under incomplete feedback.
Proceedings of the Artificial Intelligence Research and Development, 2007

2006
Regret Minimization Under Partial Monitoring.
Math. Oper. Res., 2006

The Shortest Path Problem in the Bandit Setting.
Proceedings of the 2006 IEEE Information Theory Workshop, 2006

Regret Minimization Under Partial Monitoring.
Proceedings of the 2006 IEEE Information Theory Workshop, 2006

Prediction, learning, and games.
Cambridge University Press, ISBN: 978-0-521-84108-5, 2006

2005
Minimizing regret with label efficient prediction.
IEEE Trans. Information Theory, 2005

Internal Regret in On-Line Portfolio Selection.
Machine Learning, 2005

Tracking the best quantizer.
Proceedings of the 2005 IEEE International Symposium on Information Theory, 2005

From Ranking to Classification: A Statistical View.
Proceedings of the From Data and Information Analysis to Knowledge Engineering, 2005

Tracking the Best of Many Experts.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

Ranking and Scoring Using Empirical Risk Minimization.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

2004
Efficient adaptive algorithms and minimax bounds for zero-delay lossy source coding.
IEEE Trans. Signal Processing, 2004

Efficient algorithms and minimax bounds for zero-delay lossy source coding.
Proceedings of the 2004 IEEE International Symposium on Information Theory, 2004

A "Follow the Perturbed Leader"-type Algorithm for Zero-Delay Quantization of Individual Sequence.
Proceedings of the 2004 Data Compression Conference (DCC 2004), 2004

Minimizing Regret with Label Efficient Prediction.
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

2003
Potential-Based Algorithms in On-Line Prediction and Game Theory.
Machine Learning, 2003

On the Rate of Convergence of Regularized Boosting Classifiers.
Journal of Machine Learning Research, 2003

Internal Regret in On-Line Portfolio Selection.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

Introduction to Statistical Learning Theory.
Proceedings of the Advanced Lectures on Machine Learning, 2003

Concentration Inequalities.
Proceedings of the Advanced Lectures on Machine Learning, 2003

2002
A note on robust hypothesis testing.
IEEE Trans. Information Theory, 2002

Model Selection and Error Estimation.
Machine Learning, 2002

Data-dependent margin-based generalization bounds for classification.
Journal of Machine Learning Research, 2002

A Consistent Strategy for Boosting Algorithms.
Proceedings of the Computational Learning Theory, 2002

2001
A zero-delay sequential scheme for lossy coding of individual sequences.
IEEE Trans. Information Theory, 2001

Worst-Case Bounds for the Logarithmic Loss of Predictors.
Machine Learning, 2001

Data-Dependent Margin-Based Generalization Bounds for Classification.
Proceedings of the Computational Learning Theory, 2001

Potential-Based Algorithms in Online Prediction and Game Theory.
Proceedings of the Computational Learning Theory, 2001

2000
Finite-time lower bounds for the two-armed bandit problem.
IEEE Trans. Automat. Contr., 2000

A sharp concentration inequality with applications.
Random Struct. Algorithms, 2000

Model Selection and Error Estimation.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

1999
A simple randomized algorithm for sequential prediction of ergodic time series.
IEEE Trans. Information Theory, 1999

Minimax Regret Under log Loss for General Classes of Experts.
Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 1999

1998
Learning Pattern Classification - A Survey.
IEEE Trans. Information Theory, 1998

The Minimax Distortion Redundancy in Empirical Quantizer Design.
IEEE Trans. Information Theory, 1998

Strong Minimax Lower Bounds for Learning.
Machine Learning, 1998

Scale-sensitive Dimensions and Skeleton Estimates for Classification.
Discrete Applied Mathematics, 1998

On Sequential Prediction of Individual Sequences Relative to a Set of Experts.
Proceedings of the Eleventh Annual Conference on Computational Learning Theory, 1998

1997
Empirical quantizer design in the presence of source noise or channel noise.
IEEE Trans. Information Theory, 1997

A Minimax Lower Bound for Empirical Quantizer Design.
Proceedings of the Computational Learning Theory, Third European Conference, 1997

1996
Nonparametric estimation and classification using radial basis function nets and empirical risk minimization.
IEEE Trans. Neural Networks, 1996

Concept learning using complexity regularization.
IEEE Trans. Information Theory, 1996

Designing Vector Quantizers in the Presence of Source Noise or Channel Noise.
Proceedings of the 6th Data Compression Conference (DCC '96), Snowbird, Utah, USA, March 31, 1996

A Data-Dependent Skeleton Estimate for Learning.
Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

Strong Minimax Lower Bounds for Learning.
Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

1995
Nonparametric estimation via empirical risk minimization.
IEEE Trans. Information Theory, 1995

Fixed-rate universal lossy source coding and rates of convergence for memoryless sources.
IEEE Trans. Information Theory, 1995

Lower bounds in pattern recognition and learning.
Pattern Recognition, 1995

1994
On the posterior-probability estimate of the error rate of nonparametric classification rules.
IEEE Trans. Information Theory, 1994

Rates of convergence in the source coding theorem, in empirical quantizer design, and in universal lossy source coding.
IEEE Trans. Information Theory, 1994

Nonparametric classification using radial basis function nets and empirical risk minimization.
Proceedings of the 12th IAPR International Conference on Pattern Recognition, 1994

1993
Strong universal consistency of neural network classifiers.
IEEE Trans. Information Theory, 1993

Fast Nearest-Neighbor Search in Dissimilarity Spaces.
IEEE Trans. Pattern Anal. Mach. Intell., 1993

Universality and Rates of Convergence in Lossy Source Coding.
Proceedings of the IEEE Data Compression Conference, 1993

1992
Learning with an unreliable teacher.
Pattern Recognition, 1992


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