Daniil Ryabko
daniil@ryabko.net

SequeL lab of INRIA LNE, Lille, France.
currently on sabbatical at
INRIA Chile,
Santiago de Chile




Selected publications

2014

R. Ortner, D. Ryabko, P. Auer and R. Munos, Regret Bounds for Restless Markov Bandits. bib  |  pdf
Theoretical Computer Science, to appear.
A. Khaleghi, D. Ryabko, Asymptotically consistent estimation of the number of change points in highly dependent time series. bib  |  pdf
In Proceedings of ICML, JMLR W&CP 32(1):539-547, Beijing, China, 2014.

2013

D. Ryabko, J. Mary, A Binary-Classification-Based Metric between Time-Series Distributions and Its Use in Statistical and Learning Problems. bib  |  pdf
Journal of Machine Learning Research, vol. 14: 2837-2856, 2013.
A. Khaleghi, D. Ryabko, Nonparametric multiple change point estimation in highly dependent time series. bib  |  pdf
In Proceedings of ALT, LNCS 8139, pages 382-396, Singapore, 2013.
D. Ryabko, Unsupervised model-free representation learning. bib  |  pdf (tr version)
In Proceedings of ALT, LNCS 8139, pages 354-366, Singapore, 2013.
D. Ryabko, Time-series information and learning. bib  |  pdf
In Proceedings of ISIT, pages 1392-1395, Istanbul, Turkey, 2013.
O. Maillard, P. Nguyen, R. Ortner, D. Ryabko, Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning. bib  |  pdf
In Proceedings of ICML, JMLR W&CP 28(1):543-551, Atlanta, USA, 2013.

2012

D. Ryabko, Testing composite hypotheses about discrete ergodic processes. bib  |  pdf
Test, vol. 21(2), pp. 317-329, 2012.
D. Ryabko, Uniform hypothesis testing for finite-valued stationary processes. bib  |  pdf
Statistics vol. 48(1), pp. 121-128, 2014.
A. Khaleghi, D. Ryabko, Locating Changes in Highly Dependent Data with Unknown Number of Change Points. bib  |  pdf
In Proceedings of NIPS, pp. 3095--3103, Lake Tahoe, USA, 2012.
R. Ortner, D. Ryabko, Online Regret Bounds for Undiscounted Continuous Reinforcement Learning. bib  |  pdf
In Proceedings of NIPS, pp. 1772--1780, Lake Tahoe, USA, 2012.
A. Khaleghi, D. Ryabko, J. Mary, P. Preux, Online Clustering of Processes bib  |  pdf
In Proceedings of AISTATS 2012, La Palma, Canary Islands, Spain, JMLR W&CP 22: 601-609, 2012.

2011

D. Ryabko, On the relation between realizable and non-realizable cases of the sequence prediction problem. bib  |  pdf
Journal of Machine Learning Research, vol. 12: 2161-2180, 2011.
B. Ryabko, D. Ryabko, Constructing perfect steganographic systems, bib  |  pdf
Information and Computation, 2011, Vol. 209, No. 9, pp. 1223-1230.
O. Maillard, R. Munos, D. Ryabko, Selecting the State-Representation in Reinforcement Learning bib  |  pdf
In Proceedings of NIPS, Granada, Spain, pp. 2627-2635, 2011.
B. Ryabko, D. Ryabko, Confidence Sets in Time-Series Filtering. bib  |  pdf
In Proceedings of IEEE International Symposium on Information Theory (ISIT'11), St. Petersburg, Russia, pp. 2436-2438, 2011.

2010

D. Ryabko, On Finding Predictors for Arbitrary Families of Processes. bib  |  pdf
Journal of Machine Learning Research, vol. 11(Feb): 581-602, 2010.
D. Ryabko, B. Ryabko Nonparametric Statistical Inference for Ergodic Processes, bib  |  pdf
IEEE Transactions on Information Theory, 56(3):1430-1435, 2010.
D. Ryabko, Discrimination between B-processes is impossible, bib  |  pdf
Journal of Theoretical Probability, 23(2):565-575, 2010.
D. Ryabko. Sequence prediction in realizable and non-realizable cases, bib  |  pdf
In Proceedings of The 23rd Annual Conference on Learning Theory (COLT), Haifa, Israel, pp. 119-131, 2010.
D. Ryabko. Clustering processes, bib  |  pdf
In Proceedings of 27th International Conference on Machine Learning (ICML), Haifa, Israel, pp. 919-926, 2010

2009 and before

selected journal papers
B. Ryabko, D. Ryabko, Asymptotically Optimal Perfect Steganographic Systems. bib  |  pdf
Problems of Information Transmission, 2009, Vol. 45, No. 2, pp. 184-190.
D. Ryabko, J. Schmidhuber Using data compressors to construct order tests for homogeneity and component independence, bib  |  pdf
Applied Mathematics Letters, 22:7, 1029-1032, 2009.
D. Ryabko, M. Hutter. On the Possibility of Learning in Reactive Environments with Arbitrary Dependence. bib  |  pdf
Theoretical Computer Science, Vol. 405, pp. 274-284, 2008.
D. Ryabko, M. Hutter. Predicting Non-Stationary Processes. bib  |  tr pdf
Applied Mathematics Letters Vol. 21(5) pp 477-482, 2008.
D. Ryabko. On sample complexity for computational classification problems, bib  |  pdf
Algorithmica, 49:1 (Sept): 69-77, 2007.
D. Ryabko. Pattern Recognition for Conditionally Independent Data, bib  |  pdf
Journal of Machine Learning Research 7(Apr):645-664, 2006.
A. Gutman, D. Ryabko Nonstandard hull of a normed space in a Boolean-valued universe. bib  |  pdf
Siberian Advances in Mathematics, Vol. 12 No 2, pp 38-47, 2002.

Theses

D. Ryabko. Learnability in Problems of Sequential Inference (HDR Thesis) bib  |  pdf
Université Lille 1 - Sciences et Technologies, 2011.
D. Ryabko. On the Flexibility of Theoretical Models for Pattern Recognition (Ph.D. Thesis) bib  |  pdf
Royal Holloway, University of London. April, 2005.
D. Ryabko On Some Properties of Continuous Polyverse (Ph.D. Thesis) bib  |  pdf (in Russian)
Novosibirsk State University, Sobolev Institute of Mathematics; Novosibirsk, Russia, 2003.

Selected students

Azadeh Khaleghi, On Some Unsupervised Learning Problems for Highly Dependent Time Series, pdf
PhD 2010-2013.