Optimal best arm identification with fixed confidence
We give a complete characterization of the complexity of best-arm identification in one-
parameter bandit problems. We prove a new, tight lower bound on the sample complexity …
parameter bandit problems. We prove a new, tight lower bound on the sample complexity …
Context tree selection and linguistic rhythm retrieval from written texts
Data set and scripts. The directory SUPPLEMENT [Galves et al.(2011)] contains two
subdirectories DATA and SCRIPTS. The directory named DATA contains the samples used …
subdirectories DATA and SCRIPTS. The directory named DATA contains the samples used …
Identification of nonlinear time-varying systems using an online sliding-window and common model structure selection (CMSS) approach with applications to EEG
The identification of nonlinear time-varying systems using linear-in-the-parameter models is
investigated. An efficient common model structure selection (CMSS) algorithm is proposed …
investigated. An efficient common model structure selection (CMSS) algorithm is proposed …
Informational confidence bounds for self-normalized averages and applications
A Garivier - 2013 IEEE Information Theory Workshop (ITW), 2013 - ieeexplore.ieee.org
We present deviation bounds for self-normalized averages and applications to estimation
with a random number of observations. The results rely on a peeling argument in …
with a random number of observations. The results rely on a peeling argument in …
Context-tree weighting and Bayesian Context Trees: Asymptotic and non-asymptotic justifications
I Kontoyiannis - IEEE Transactions on Information Theory, 2023 - ieeexplore.ieee.org
The Bayesian Context Trees (BCT) framework is a recently introduced, general collection of
statistical and algorithmic tools for modelling, analysis and inference with discrete-valued …
statistical and algorithmic tools for modelling, analysis and inference with discrete-valued …
[HTML][HTML] Context tree selection: A unifying view
Context tree models have been introduced by Rissanen in [25] as a parsimonious
generalization of Markov models. Since then, they have been widely used in applied …
generalization of Markov models. Since then, they have been widely used in applied …
Stochastic chains with memory of variable length
A Galves, E Löcherbach - arxiv preprint arxiv:0804.2050, 2008 - arxiv.org
Stochastic chains with memory of variable length constitute an interesting family of
stochastic chains of infinite order on a finite alphabet. The idea is that for each past, only a …
stochastic chains of infinite order on a finite alphabet. The idea is that for each past, only a …
Reducing the space complexity of a Bayes coding algorithm using an expanded context tree
T Matsushima, S Hirasawa - 2009 IEEE International …, 2009 - ieeexplore.ieee.org
The context tree models are widely used in a lot of research fields. Patricia like trees are
applied to the context trees that are expanded according to the increase of the length of a …
applied to the context trees that are expanded according to the increase of the length of a …
Stationary and transition probabilities in slow mixing, long memory markov processes
M Asadi, RP Torghabeh… - IEEE Transactions on …, 2014 - ieeexplore.ieee.org
We observe a length-n sample generated by an unknown, stationary ergodic Markov
process (model) over a finite alphabet A. Given any string w of symbols from A we want …
process (model) over a finite alphabet A. Given any string w of symbols from A we want …
Fast parallel construction of variable-length Markov chains
Background Alignment-free methods are a popular approach for comparing biological
sequences, including complete genomes. The methods range from probability distributions …
sequences, including complete genomes. The methods range from probability distributions …