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We revisit the classical problem of universal prediction of stochastic sequences with a finite time horizon $T$ known to the learner. The question we investigate is whether it is possible to derive vanishing regret bounds that hold with…

Machine Learning · Computer Science 2026-02-19 Matthias Frey , Jonathan H. Manton , Jingge Zhu

This work prepares new probability bounds for sums of random, independent, Hermitian tensors. These probability bounds characterize large-deviation behavior of the extreme eigenvalue of the sums of random tensors. We extend Lapalace…

Probability · Mathematics 2021-01-01 Shih Yu Chang

Uncertainty often plays an important role in dynamic flow problems. In this paper, we consider both, a stationary and a dynamic flow model with uncertain boundary data on networks. We introduce two different ways how to compute the…

Numerical Analysis · Mathematics 2021-04-28 Michael Schuster , Elisa Strauch , Martin Gugat , Jens Lang

We present a general approach to deriving bounds on the generalization error of randomized learning algorithms. Our approach can be used to obtain bounds on the average generalization error as well as bounds on its tail probabilities, both…

Information Theory · Computer Science 2020-09-10 Fredrik Hellström , Giuseppe Durisi

The probability that the sum of independent, centered, identically distributed, heavy-tailed random variables achieves a very large value is asymptotically equal to the probability that there exists a single summand equalling that value. We…

Probability · Mathematics 2024-02-15 Quirin Vogel

In semidefinite programming a proposed optimal solution may be quite poor in spite of having sufficiently small residual in the optimality conditions. This issue may be framed in terms of the discrepancy between forward error (the…

Optimization and Control · Mathematics 2019-08-14 Stefan Sremac , Hugo J. Woerdeman , Henry Wolkowicz

The analysis of random coding error exponents pertaining to erasure/list decoding, due to Forney, is revisited. Instead of using Jensen's inequality as well as some other inequalities in the derivation, we demonstrate that an exponentially…

Information Theory · Computer Science 2016-11-17 Neri Merhav

Numerical precision in large-scale scientific computations has become an emerging topic due to recent developments in computer hardware. Lower floating point precision offers the potential for significant performance improvements, but the…

Fluid Dynamics · Physics 2025-05-05 Martin Karp , Niclas Jansson , Saleh Rezaeiravesh , Stefano Markidis , Philipp Schlatter

Many probabilistic programming languages allow programs to be run under constraints in order to carry out Bayesian inference. Running programs under constraints could enable other uses such as rare event simulation and probabilistic…

Programming Languages · Computer Science 2015-01-19 Neil Toronto , Jay McCarthy , David Van Horn

Reliable probabilistic primality tests are fundamental in public-key cryptography. In adversarial scenarios, a composite with a high probability of passing a specific primality test could be chosen. In such cases, we need worst-case error…

Cryptography and Security · Computer Science 2023-06-19 Semira Einsele , Kenneth Paterson

We consider the state-minimisation problem for weighted and probabilistic automata. We provide a numerically stable polynomial-time minimisation algorithm for weighted automata, with guaranteed bounds on the numerical error when run with…

Formal Languages and Automata Theory · Computer Science 2014-05-02 Stefan Kiefer , Björn Wachter

Given a real symmetric positive semi-definite matrix E, and an approximation S that is a sum of n independent matrix-valued random variables, we present bounds on the relative error in S due to randomization. The bounds do not depend on the…

Numerical Analysis · Mathematics 2018-01-03 John T. Holodnak , Ilse C. F. Ipsen , Ralph C. Smith

Asymptotics deviation probabilities of the sum S n = X 1 + $\times$ $\times$ $\times$ + X n of independent and identically distributed real-valued random variables have been extensively investigated, in particular when X 1 is not…

Probability · Mathematics 2021-01-21 Fabien Brosset , Thierry Klein , Agnès Lagnoux , Pierre Petit

This paper establishes sharp dimension-free concentration inequalities and expectation bounds for the deviation of the sum of simple random tensors from its expectation. As part of our analysis, we use generic chaining techniques to obtain…

Probability · Mathematics 2025-09-30 Omar Al-Ghattas , Jiaheng Chen , Daniel Sanz-Alonso

We study online aggregation of the predictions of experts, and first show new second-order regret bounds in the standard setting, which are obtained via a version of the Prod algorithm (and also a version of the polynomially weighted…

Machine Learning · Statistics 2014-02-11 Pierre Gaillard , Gilles Stoltz , Tim Van Erven

We construct examples of degree-two U- and V-statistics of $n$ i.i.d.~heavy-tailed random vectors in $\mathbb{R}^{d(n)}$, whose $\nu$-th moments exist for ${\nu > 2}$, and provide tight bounds on the error of approximating both statistics…

Statistics Theory · Mathematics 2024-06-19 Kevin Han Huang , Peter Orbanz

For any pair $(X,Z)$ of correlated random variables we can think of $Z$ as a randomized function of $X$. Provided that $Z$ is short, one can make this function computationally efficient by allowing it to be only approximately correct. In…

Cryptography and Security · Computer Science 2016-07-18 Maciej Skorski

It is well known that the computation of accurate trajectories of the Lorenz system is a difficult problem. Computed solutions are very sensitive to the discretization error determined by the time step size and polynomial order of the…

Numerical Analysis · Mathematics 2013-06-13 Benjamin Kehlet , Anders Logg

The bounds for absolute moments of order statistics are established. Let $X_1,\dots ,X_n$ be independent identically distributed real-valued random variables and let $X_{1:n}\le \dots \le X_{n:n}$ be the corresponding order statistics. The…

Probability · Mathematics 2016-08-01 Nadezhda V. Gribkova

Elementary function calls are a common feature in numerical programs. While their implementions in library functions are highly optimized, their computation is nonetheless very expensive compared to plain arithmetic. Full accuracy is,…

Numerical Analysis · Computer Science 2018-11-27 Eva Darulova , Anastasia Volkova