44 citations · 238 across the 35 of their papers we have counts for
21 papers · 1 filter
Universal time-series forecasting with mixture predictors
Daniil Ryabko
This book is devoted to the problem of sequential probability forecasting, that is, predicting the probabilities of the next outcome of a growing sequence of observations given the…
Finite-time optimality of Bayesian predictors
Daniil Ryabko
The problem of sequential probability forecasting is considered in the most general setting: a model set C is given, and it is required to predict as well as possible if any of the…
Hypotheses testing on infinite random graphs
Daniil Ryabko
Drawing on some recent results that provide the formalism necessary to definite stationarity for infinite random graphs, this paper initiates the study of statistical and learning…
Independence clustering (without a matrix)
Daniil Ryabko
The independence clustering problem is considered in the following formulation: given a set of random variables, it is required to find the finest partitioning $\{U_1,\dots,U_k…
Things Bayes can't do
Daniil Ryabko
The problem of forecasting conditional probabilities of the next event given the past is considered in a general probabilistic setting. Given an arbitrary (large, uncountable) set…
Characterizing predictable classes of processes
Daniil Ryabko
The problem is sequence prediction in the following setting. A sequence x1,..., xn,... of discrete-valued observations is generated according to some unknown probabilistic law (mea…