Daniil Ryabko
18 papers · 2006–2019 · 5 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (25) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Deep Specialist
(10)
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Keyword Champion
(5)
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Trend Setter
π₯
Unstoppable Β· Bronze
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Conference Pioneer
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Century Club Β· Bronze
ποΈ
Keyword Collector
(82)
Top co-authors
Research topics
Machine Learning
(17)
Optimization & Theory
(15)
Core Methods
(8)
Learning Types
(8)
Data Science & Analytics
(6)
Methods Β· Data Science & Analytics
(6)
Mathematics & Optimization
(4)
Reinforcement Learning
(4)
Methods Β· Reinforcement Learning
(4)
Applications
(3)
Optimization
(2)
Artificial Intelligence
(1)
Bayesian & Probabilistic
(1)
Core AI
(1)
Mathematics
(1)
Keywords
regret bound
(6)
time series analysis
(5)
reinforcement learning
(4)
markov decision process
(3)
ergodic process
(3)
state representation
(3)
stationary ergodic
(3)
asymptotic consistency
(3)
online learning
(3)
sequence prediction
(2)
binary classification
(2)
change point detection
(2)
metric learning
(2)
time series clustering
(2)
continuous state space
(2)
unsupervised learning
(2)
time series
(2)
optimal policy
(2)
model selection
(2)
homogeneity testing
(2)
Papers
On Asymptotic and Finite-Time Optimality of Bayesian Predictors
JMLR 2019
Hypotheses testing on infinite random graphs
ALT 2017
Independence clustering (without a matrix)
NeurIPS 2017
Universality of Bayesian mixture predictors
ALT 2017
Consistent Algorithms for Clustering Time Series
JMLR 2016
Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning
ICML 2015
Asymptotically consistent estimation of the number of change points in highly dependent time series
ICML 2014
A Binary-Classification-Based Metric between Time-Series Distributions and Its Use in Statistical and Learning Problems
JMLR 2013
Competing with an Infinite Set of Models in Reinforcement Learning
AISTATS 2013
Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning
ICML 2013
Locating Changes in Highly Dependent Data with Unknown Number of Change Points
NeurIPS 2012
Online Clustering of Processes
AISTATS 2012
Online Regret Bounds for Undiscounted Continuous Reinforcement Learning
NeurIPS 2012
Reducing statistical time-series problems to binary classification
NeurIPS 2012
On the Relation between Realizable and Nonrealizable Cases of the Sequence Prediction Problem
JMLR 2011
Selecting the State-Representation in Reinforcement Learning
NeurIPS 2011
On Finding Predictors for Arbitrary Families of Processes
JMLR 2010
Pattern Recognition for Conditionally Independent Data
JMLR 2006