
Hierarchical Bayesian Mixture Models for Time Series Using Context Trees as State Space Partitions
A general Bayesian framework is introduced for mixture modelling and inf...
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Entropy and the Discrete Central Limit Theorem
A strengthened version of the central limit theorem for discrete random ...
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Inferring community characteristics in labelled networks
Labelled networks form a very common and important class of data, natura...
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An InformationTheoretic Proof of a Finite de Finetti Theorem
A finite form of de Finetti's representation theorem is established usin...
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Compression and Symmetry of SmallWorld Graphs and Structures
For various purposes and, in particular, in the context of data compress...
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Bayesian Context Trees: Modelling and exact inference for discrete time series
We develop a new Bayesian modelling framework for the class of higheror...
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Sharp SecondOrder Pointwise Asymptotics for Lossless Compression with Side Information
The problem of determining the best achievable performance of arbitrary ...
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Optimal rates for independence testing via Ustatistic permutation tests
We study the problem of independence testing given independent and ident...
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The Lévy State Space Model
In this paper we introduce a new class of state space models based on sh...
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Fundamental Limits of Lossless Data Compression with Side Information
The problem of lossless data compression with side information available...
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Differential Temporal Difference Learning
Value functions derived from Markov decision processes arise as a centra...
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A Simple Network of Nodes Moving on the Circle
Two simple Markov processes are examined, one in discrete and one in con...
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Nonasymptotic Gaussian Approximation for Linear Systems with Stable Noise [Preliminary Version]
The results of a series of theoretical studies are reported, examining t...
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Analysis of Geographic/DelayTolerant Routing in Mobile Wireless Networks
A mobile wireless delaytolerant network (DTN) model is proposed and ana...
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Ioannis Kontoyiannis
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