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In this paper we study the notion of estimation entropy recently established by Liberzon and Mitra. This quantity measures the smallest rate of information about the state of a dynamical system above which an exponential state estimation…

Dynamical Systems · Mathematics 2017-05-08 Christoph Kawan

In this paper, we consider the finite-state approximation of a discrete-time constrained Markov decision process (MDP) under the discounted and average cost criteria. Using the linear programming formulation of the constrained discounted…

Optimization and Control · Mathematics 2018-07-10 Naci Saldi

I formulate an entropy-rate maximization problem at the observable level for stochastic processes observed through an information-reducing observation map. For a visible stationary law, the map determines an observational fiber of hidden…

Information Theory · Computer Science 2026-04-14 Oleg Kiriukhin

A random phase property establishing a link between quasi-one-dimensional random Schroedinger operators and full random matrix theory is advocated. Briefly summarized it states that the random transfer matrices placed into a normal system…

Mathematical Physics · Physics 2010-06-04 Rudolf A Roemer , Hermann Schulz-Baldes

Discrete stationary classical processes as well as quantum lattice states are asymptotically confined to their respective typical support, the exponential growth rate of which is given by the (maximal ergodic) entropy. In the iid case the…

Probability · Mathematics 2009-11-13 I. Bjelakovic , J. -D. Deuschel , T. Krueger , R. Seiler , Ra. Siegmund-Schultze , A. Szkola

In this paper we characterize the distribution of the first exit time from an arbitrary open set for a class of semi-Markov processes obtained as time-changed Markov processes. We estimate the asymptotic behaviour of the survival function…

Probability · Mathematics 2019-03-05 Giacomo Ascione , Enrica Pirozzi , Bruno Toaldo

We show how Markov mixed membership models (MMMM) can be used to predict the degradation of assets. We model the degradation path of individual assets, to predict overall failure rates. Instead of a separate distribution for each hidden…

Machine Learning · Computer Science 2020-06-03 Paul Hofmann , Zaid Tashman

This work studies the (non)robustness of two-layer neural networks in various high-dimensional linearized regimes. We establish fundamental trade-offs between memorization and robustness, as measured by the Sobolev-seminorm of the model…

Machine Learning · Statistics 2021-06-07 Elvis Dohmatob

We present new lower and upper bounds for the compression rate of binary prefix codes optimized over memoryless sources according to two related exponential codeword length objectives. The objectives explored here are exponential-average…

Information Theory · Computer Science 2011-05-03 Michael B. Baer

We present two approaches for linear prediction of long-memory time series. The first approach consists in truncating the Wiener-Kolmogorov predictor by restricting the observations to the last $k$ terms, which are the only available values…

Statistics Theory · Mathematics 2007-05-23 Fanny Godet

In this note, we show that the Lyapunov exponents of mixed products of random truncated Haar unitary and complex Ginibre matrices are asymptotically given by equally spaced `picket-fence' statistics. We discuss how these statistics should…

Probability · Mathematics 2022-02-01 Andrew Ahn , Roger Van Peski

Recently, Samorodnitsky proved a strengthened version of Mrs. Gerber's Lemma, where the output entropy of a binary symmetric channel is bounded in terms of the average entropy of the input projected on a random subset of coordinates. Here,…

Information Theory · Computer Science 2016-05-11 Or Ordentlich

We study the singular values and Lyapunov exponents of non-stationary random matrix products subject to small, absolutely continuous, additive noise. Consider a fixed sequence of matrices of bounded norm. Independently perturb the matrices…

Probability · Mathematics 2025-12-22 Sam Bednarski , Jonathan DeWitt , Anthony Quas

The impact of randomness on model training is poorly understood. How do differences in data order and initialization actually manifest in the model, such that some training runs outperform others or converge faster? Furthermore, how can we…

Machine Learning · Computer Science 2024-01-23 Michael Y. Hu , Angelica Chen , Naomi Saphra , Kyunghyun Cho

The goal of the paper is to study asymptotic behavior of the number of lost messages. Long messages are assumed to be divided into a random number of packets which are transmitted independently of one another. An error in transmission of a…

Probability · Mathematics 2007-05-23 Vyacheslav M. Abramov

We present an efficient exact algorithm for estimating state sequences from outputs (or observations) in imprecise hidden Markov models (iHMM), where both the uncertainty linking one state to the next, and that linking a state to its…

Artificial Intelligence · Computer Science 2012-10-08 Jasper De Bock , Gert de Cooman

If the dynamics of an open quantum systems is non-Markovian, its {asymptotic} state strongly depends on the initial conditions, even if the dynamics possesses an {invariant} state. This is the very essence of memory effects. In particular,…

Quantum Physics · Physics 2010-11-29 Dariusz Chruściński , Andrzej Kossakowski , Saverio Pascazio

In this paper we consider the problem of estimating a Bernoulli parameter using finite memory. Let $X_1,X_2,\ldots$ be a sequence of independent identically distributed Bernoulli random variables with expectation $\theta$, where $\theta \in…

Information Theory · Computer Science 2022-06-22 Tomer Berg , Or Ordentlich , Ofer Shayevitz

Many non-equilibrium, active processes are observed at a coarse-grained level, where different microscopic configurations are projected onto the same observable state. Such "lumped" observables display memory, and in many cases the…

Statistical Mechanics · Physics 2024-04-29 Kristian Blom , Kevin Song , Etienne Vouga , Aljaž Godec , Dmitrii E. Makarov

For a certain class of isolated quantum systems, we report the existence of irreversible processes in which the energy is not dissipated. After a closed cycle in which the initial energy distribution is fully recovered, the expectation…

Quantum Physics · Physics 2015-09-30 Ricardo Puebla , Armando Relaño