Ryabko, Daniil

32 publications

JMLR 2019 On Asymptotic and Finite-Time Optimality of Bayesian Predictors Daniil Ryabko

ALT 2017 Hypotheses Testing on Infinite Random Graphs Daniil Ryabko

NeurIPS 2017 Independence Clustering (without a Matrix) Daniil Ryabko

ALT 2017 Universality of Bayesian Mixture Predictors Daniil Ryabko

JMLR 2016 Consistent Algorithms for Clustering Time Series Azadeh Khaleghi, Daniil Ryabko, Jérémie Mary, Philippe Preux

ALT 2016 Things Bayes Can't Do Daniil Ryabko

ICML 2015 Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning K. Lakshmanan, Ronald Ortner, Daniil Ryabko

ICML 2014 Asymptotically Consistent Estimation of the Number of Change Points in Highly Dependent Time Series Azadeh Khaleghi, Daniil Ryabko

ALT 2014 Selecting Near-Optimal Approximate State Representations in Reinforcement Learning Ronald Ortner, Odalric-Ambrym Maillard, Daniil Ryabko

JMLR 2013 A Binary-Classification-Based Metric Between Time-Series Distributions and Its Use in Statistical and Learning Problems Daniil Ryabko, Jérémie Mary

AISTATS 2013 Competing with an Infinite Set of Models in Reinforcement Learning Phuong Nguyen, Odalric-Ambrym Maillard, Daniil Ryabko, Ronald Ortner

ALT 2013 Nonparametric Multiple Change Point Estimation in Highly Dependent Time Series Azadeh Khaleghi, Daniil Ryabko

ICML 2013 Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning Odalric-Ambrym Maillard, Phuong Nguyen, Ronald Ortner, Daniil Ryabko

ALT 2013 Unsupervised Model-Free Representation Learning Daniil Ryabko

NeurIPS 2012 Locating Changes in Highly Dependent Data with Unknown Number of Change Points Azadeh Khaleghi, Daniil Ryabko

AISTATS 2012 Online Clustering of Processes Azadeh Khaleghi, Daniil Ryabko, Jeremie Mary, Philippe Preux

NeurIPS 2012 Online Regret Bounds for Undiscounted Continuous Reinforcement Learning Ronald Ortner, Daniil Ryabko

NeurIPS 2012 Reducing Statistical Time-Series Problems to Binary Classification Daniil Ryabko, Jeremie Mary

ALT 2012 Regret Bounds for Restless Markov Bandits Ronald Ortner, Daniil Ryabko, Peter Auer, Rémi Munos

JMLR 2011 On the Relation Between Realizable and Nonrealizable Cases of the Sequence Prediction Problem Daniil Ryabko

NeurIPS 2011 Selecting the State-Representation in Reinforcement Learning Odalric-ambrym Maillard, Daniil Ryabko, Rémi Munos

ICML 2010 Clustering Processes Daniil Ryabko

JMLR 2010 On Finding Predictors for Arbitrary Families of Processes Daniil Ryabko

COLT 2010 Sequence Prediction in Realizable and Non-Realizable Cases Daniil Ryabko

UAI 2009 Characterizing Predictable Classes of Processes Daniil Ryabko

ICML 2009 Workshop Summary: On-Line Learning with Limited Feedback Jean-Yves Audibert, Peter Auer, Alessandro Lazaric, Rémi Munos, Daniil Ryabko, Csaba Szepesvári

ALT 2008 Some Sufficient Conditions on an Arbitrary Class of Stochastic Processes for the Existence of a Predictor Daniil Ryabko

ALT 2006 Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence Daniil Ryabko, Marcus Hutter

JMLR 2006 Pattern Recognition for Conditionally Independent Data Daniil Ryabko

ALT 2005 On Computability of Pattern Recognition Problems Daniil Ryabko

ALT 2004 Application of Classical Nonparametric Predictors to Learning Conditionally I.I.D. Data Daniil Ryabko

ICML 2004 Online Learning of Conditionally I.I.D. Data Daniil Ryabko