Daniil Ryabko
daniil@ryabko.net






Selected papers

2017

D. Ryabko, Independence clustering (without a matrix). bib  |  pdf
In Proceedings of NIPS, Long Beach, USA, 2017.
D. Ryabko, Hypotheses testing on infinite random graphs. bib  |  pdf
In Proceedings of ALT, Kyoto, Japan, 2017.
D. Ryabko, Universality of Bayesian mixture predictors. bib pdf
In Proceedings of ALT, Kyoto, Japan, 2017.

2016

D. Ryabko, Things Bayes can't do. bib  |  pdf
In Proceedings of ALT, LNCS 9925, pp.253-260, Bari, Italy, 2016.
A. Khaleghi, D. Ryabko, J. Mary, Ph. Preux, Consistent Algorithms for Clustering Time Series. bib  |  pdf
Journal of Machine Learning Research, 17(3):1-32, 2016.

2015

A. Khaleghi, D. Ryabko, Nonparametric multiple change point estimation in highly dependent time series. bib  |  pdf
Theoretical Computer Science, 620:119-133, 2016.
D. Ryabko, B. Ryabko, Predicting the outcomes of every process for which an asymptotically accurate stationary predictor exists is impossible, bib  |  pdf
In Proceedings of ISIT, pp. 1204-1206, Hong Kong, 2015.
D. Ryabko, Zh. Reznikova, On the evolutionary origins of differences in sexual preferences. bib  |  pdf
Frontiers in Psychology, 6:628.

2014

R. Ortner, O. Maillard, D. Ryabko, Selecting Near-Optimal Approximate State Representations in Reinforcement Learning. bib  |  pdf
In Proceedings of ALT, LNCS 8776, pp. 140-154, Bled, Slovenia, 2014.
R. Ortner, D. Ryabko, P. Auer and R. Munos, Regret Bounds for Restless Markov Bandits. bib  |  pdf
Theoretical Computer Science, 558:62-76, 2014.
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.
D. Ryabko, Time-series information and learning. bib  |  pdf
In Proceedings of ISIT, pages 1392-1395, Istanbul, Turkey, 2013.
D. Ryabko, Unsupervised model-free representation learning. bib  |  pdf
In Proceedings of ALT, LNCS 8139, pages 354-366, Singapore, 2013.
O. Maillard, Ph. 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.

2011 and before
selected journal papers

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.
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, 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, vol.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.