Daniil Ryabko

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

Locating Changes in Highly Dependent Data with Unknown Number of Change Points.

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[DOI]

Azadeh Khaleghi

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

On the Relation between Realizable and Nonrealizable Cases of the Sequence Prediction Problem.

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[DOI]

J. Mach. Learn. Res., 2011

Constructing perfect steganographic systems.

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[DOI]

Inf. Comput., 2011

Selecting the State-Representation in Reinforcement Learning.

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[DOI]

Odalric-Ambrym Maillard

Rémi Munos

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

Confidence sets in time-series filtering.

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[DOI]

Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

Learnability in Problems of Sequential Inference. (Apprenabilité dans les ProblèMES de l'inféRence SéQuentielle).

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[DOI]

, 2011

2010

Nonparametric statistical inference for ergodic processes.

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[DOI]

IEEE Trans. Inf. Theory, 2010

On Finding Predictors for Arbitrary Families of Processes.

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[DOI]

J. Mach. Learn. Res., 2010

Clustering processes.

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[DOI]

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

Sequence Prediction in Realizable and Non-realizable Cases.

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[DOI]

Proceedings of the COLT 2010, 2010

2009

Asymptotically optimal perfect steganographic systems.

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[DOI]

B. Ya. Ryabko

Probl. Inf. Transm., 2009

A criterion for hypothesis testing for stationary processes

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[DOI]

CoRR, 2009

Using data compressors to construct order tests for homogeneity and component independence.

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[DOI]

Jürgen Schmidhuber

Appl. Math. Lett., 2009

Characterizing predictable classes of processes.

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[DOI]

Proceedings of the UAI 2009, 2009

Using Kolmogorov complexity for understanding some limitations on steganography.

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[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2009

An impossibility result for process discrimination.

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[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2009

Workshop summary: On-line learning with limited feedback.

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[DOI]

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

2008

On the possibility of learning in reactive environments with arbitrary dependence.

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[DOI]

Theor. Comput. Sci., 2008

Testing Statistical Hypotheses About Ergodic Processes

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[DOI]

CoRR, 2008

Predicting non-stationary processes.

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[DOI]

Appl. Math. Lett., 2008

On hypotheses testing for ergodic processes.

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[DOI]

Proceedings of the 2008 IEEE Information Theory Workshop, 2008

Some Sufficient Conditions on an Arbitrary Class of Stochastic Processes for the Existence of a Predictor.

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[DOI]

Proceedings of the Algorithmic Learning Theory, 19th International Conference, 2008

2007

Using Data Compressors to Construct Rank Tests

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[DOI]

Jürgen Schmidhuber

CoRR, 2007

Sample Complexity for Computational Classification Problems.

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[DOI]

Algorithmica, 2007

Information-Theoretic Approach to Steganographic Systems.

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[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2007

On Sequence Prediction for Arbitrary Measures.

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[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2007

Testing Component Independence Using Data Compressors.

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[DOI]

Proceedings of the Artificial Neural Networks, 2007

2006

Pattern Recognition for Conditionally Independent Data.

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[DOI]

J. Mach. Learn. Res., 2006

Provably Secure Universal Steganographic Systems.

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[DOI]

IACR Cryptol. ePrint Arch., 2006

Learning in Reactive Environments with Arbitrary Dependence.

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[DOI]

Proceedings of the Kolmogorov Complexity and Applications, 29.01. - 03.02.2006, 2006

Sequence prediction for non-stationary processes.

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[DOI]

Proceedings of the Combinatorial and Algorithmic Foundations of Pattern and Association Discovery, 14.05., 2006

Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence.

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[DOI]

Proceedings of the Algorithmic Learning Theory, 17th International Conference, 2006

2005

On sample complexity for computational pattern recognition

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[DOI]

CoRR, 2005

On Computability of Pattern Recognition Problems.

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[DOI]

Proceedings of the Algorithmic Learning Theory, 16th International Conference, 2005

2004

Online learning of conditionally I.I.D. data.

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[DOI]

Proceedings of the Machine Learning, 2004

Application of Classical Nonparametric Predictors to Learning Conditionally I.I.D. Data.

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[DOI]