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Online Markov Decision Processes Under Bandit Feedback

IEEE transactions on automatic control, 2014-03, Vol.59 (3), p.676-691

2014

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On Codecell Convexity of Optimal Multiresolution Scalar Quantizers for Continuous Sources

IEEE transactions on information theory, 2012-02, Vol.58 (2), p.1147-1157

Antos, A.

2012

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Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path

Machine learning, 2008-04, Vol.71 (1), p.89-129

2008

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Improved minimax bounds on the test and training distortion of empirically designed vector quantizers

IEEE transactions on information theory, 2005-11, Vol.51 (11), p.4022-4032

Antos, A.

2005

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Individual convergence rates in empirical vector quantizer design

IEEE transactions on information theory, 2005-11, Vol.51 (11), p.4013-4022

2005

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Toward a classification of finite partial-monitoring games

Theoretical computer science, 2013-02, Vol.473, p.77-99

2013

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Improved Minimax Bounds on the Test and Training Distortion of Empirically Designed Vector Quantizers

Learning Theory, 2005, p.531-544

2005

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Active learning in heteroscedastic noise

Theoretical computer science, 2010-06, Vol.411 (29), p.2712-2728

2010

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Lower bounds for the rate of convergence in nonparametric pattern recognition

Theoretical computer science, 2002-07, Vol.284 (1), p.3-24

Antos, András

2002

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Convergence properties of functional estimates for discrete distributions

Random structures & algorithms, 2001-10, Vol.19 (3-4), p.163-193

2001

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Strong Minimax Lower Bounds for Learning

Machine learning, 1998-01, Vol.30 (1), p.31-56

1998

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Lower bounds for Bayes error estimation

IEEE transactions on pattern analysis and machine intelligence, 1999-07, Vol.21 (7), p.643-645

1999

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Value-Iteration Based Fitted Policy Iteration: Learning with a Single Trajectory

2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning, 2007, p.330-337

2007

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Active learning in heteroscedastic noise: Algorithmic Learning Theory (ALT 2008)

Theoretical computer science, 2010, Vol.411 (29-30), p.2712-2728

2010

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Learning Near-Optimal Policies with Bellman-Residual Minimization Based Fitted Policy Iteration and a Single Sample Path

Learning Theory, 2006, p.574-588

2006

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Lower Bounds on the Rate of Convergence of Nonparametric Pattern Recognition

Computational Learning Theory, 1999, p.241-252

1999

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Data-dependent margin-based generalization bounds for classification

Journal of machine learning research, 2003-01, Vol.3 (1), p.73-98

2003

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Rawa Trees

Mathematics and Computer Science, p.3-15

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Strong minimax lower bounds for learning

Annual Workshop on Computational Learning Theory: Proceedings of the ninth annual conference on Computational learning theory; 28 June-01 July 1996, 1996, p.303-309

1996

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Strong Minimax Lower Bounds for Learning

SSRN Electronic Journal

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Lower bounds on the rate of convergence of nonparametric regression estimates

Journal of statistical planning and inference, 2000, Vol.83 (1), p.91-100

2000

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Improved convergence rates in empirical vector quantizer design

International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings, 2004, p.300-300

2004

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Performance Limits of Nonparametric Estimators

Antos, András

1999

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Estimating the entropy of discrete distributions

Proceedings. 2001 IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252), 2001, p.45

2001

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Boosting Multitask Decomposition: Directness, Sequentiality, Subsampling, Cross-Gradients

Artificial Intelligence in Medicine, p.17-35

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Online Markov Decision Processes Under Bandit Feedback

On Codecell Convexity of Optimal Multiresolution Scalar Quantizers for Continuous Sources

Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path

Improved minimax bounds on the test and training distortion of empirically designed vector quantizers

Individual convergence rates in empirical vector quantizer design

Toward a classification of finite partial-monitoring games

Improved Minimax Bounds on the Test and Training Distortion of Empirically Designed Vector Quantizers

Active learning in heteroscedastic noise

Lower bounds for the rate of convergence in nonparametric pattern recognition

Convergence properties of functional estimates for discrete distributions

Strong Minimax Lower Bounds for Learning

Lower bounds for Bayes error estimation

Value-Iteration Based Fitted Policy Iteration: Learning with a Single Trajectory

Active learning in heteroscedastic noise: Algorithmic Learning Theory (ALT 2008)

Learning Near-Optimal Policies with Bellman-Residual Minimization Based Fitted Policy Iteration and a Single Sample Path

Lower Bounds on the Rate of Convergence of Nonparametric Pattern Recognition

Data-dependent margin-based generalization bounds for classification

Rawa Trees

Strong minimax lower bounds for learning

Strong Minimax Lower Bounds for Learning

Lower bounds on the rate of convergence of nonparametric regression estimates

Improved convergence rates in empirical vector quantizer design

Performance Limits of Nonparametric Estimators

Estimating the entropy of discrete distributions

Boosting Multitask Decomposition: Directness, Sequentiality, Subsampling, Cross-Gradients

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