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We propose a rigorous decomposition of predictive error, highlighting that not all 'irreducible' error is genuinely immutable. Many domains stand to benefit from iterative enhancements in measurement, construct validity, and modeling. Our…

Machine Learning · Computer Science 2025-02-12 Jiani Yan , Charles Rahal

This paper presents two stochastic model predictive control methods for linear time-invariant systems subject to unbounded additive uncertainties. The new methods are developed by formulating the chance constraints into deterministic form,…

Systems and Control · Electrical Eng. & Systems 2021-04-22 Fei Li , Huiping Li , Yuyao He

The Duffin-Schaeffer conjecture is a central open problem in metric number theory. Let $\psi~\mathbb{N} \mapsto \mathbb{R}$ be a non-negative function, and set $\mathcal{E}_n :=\bigcup \left( \frac{a - \psi(n)}{n},\frac{a+\psi(n)}{n}…

Number Theory · Mathematics 2019-07-11 Christoph Aistleitner

In this paper we develop necessary conditions for optimality, in the form of the stochastic Pontryagin maximum principle, for controlled equation with delay in the state and with control dependent noise, in the general case of controls $u…

Probability · Mathematics 2023-06-14 Giuseppina Guatteri , Federica Masiero

Certain Markov processes, or deterministic evolution equations, have the property that they are dual to a stochastic process that exhibits extinction versus unbounded growth, i.e., the total mass in such a process either becomes zero, or…

Probability · Mathematics 2007-05-23 Jan M. Swart

We show that for a large class of stochastic flows the spatial derivative grows at most exponentially fast even if one takes the supremum over a bounded set of initial points. We derive explicit bounds on the growth rates that depend on the…

Probability · Mathematics 2011-03-16 Holger van Bargen , Michael Scheutzow , Simon Wasserroth

For a L\'evy process $X$ on a finite time interval consider the probability that it exceeds some fixed threshold $x>0$ while staying below $x$ at the points of a regular grid. We establish exact asymptotic behavior of this probability as…

Probability · Mathematics 2022-01-05 Krzysztof Bisewski , Jevgenijs Ivanovs

We derive an upper bound on the number of models for exact satisfiability (XSAT) of arbitrary CNF formulas F. The bound can be calculated solely from the distribution of positive and negated literals in the formula. For certain subsets of…

Computational Complexity · Computer Science 2018-03-21 Bernd Schuh

In this paper, we investigate the optimal control problem for systems driven by mixed fractional Brownian motion (including a fractional Brownian motion with Hurst parameter $H>1/2$ and the standard Brownian motion). By using Malliavin…

Optimization and Control · Mathematics 2024-12-25 Yuhang Li , Yuecai Han

Let X be a nonempty convex compact subset of some Haus-dorff locally convex topological vector space S. The well know Bauer's maximum principle stats that every convex upper semi-continuous function from X into R attains its maximum at some…

Functional Analysis · Mathematics 2018-12-19 Mohammed Bachir

Let $\pa{X_{t}}_{t\in T}$ be a family of real-valued centered random variables indexed by a countable set $T$. In the first part of this paper, we establish exponential bounds for the deviation probabilities of the supremum $Z=\sup_{t\in…

Statistics Theory · Mathematics 2009-09-11 Yannick Baraud

Self-normalized processes arise naturally in statistical applications. Being unit free, they are not affected by scale changes. Moreover, self-normalization often eliminates or weakens moment assumptions. In this paper we present several…

Probability · Mathematics 2007-05-23 Victor H. de la Pena , Michael J. Klass , Tze Leung Lai

Consider the following heuristic for building a decision tree for a function $f : \{0,1\}^n \to \{\pm 1\}$. Place the most influential variable $x_i$ of $f$ at the root, and recurse on the subfunctions $f_{x_i=0}$ and $f_{x_i=1}$ on the…

Data Structures and Algorithms · Computer Science 2019-11-19 Guy Blanc , Jane Lange , Li-Yang Tan

In this paper we prove a necessary condition of the optimal control problem for a class of general mean-field forward-backward stochastic systems with jumps in the case where the diffusion coefficients depend on control, the control set…

Optimization and Control · Mathematics 2019-02-20 Tao Hao , Qingxin Meng

In this article, we provide upper and lower bounds for the growth rate of irreducible meanders. The obtained upper bound implies that the proportion of irreducible meanders among all of the prime meanders of order $n$ approaches $0$ as $n$…

Combinatorics · Mathematics 2021-12-21 Y. Belousov , A. Malyutin

We investigate the (functional) convex order of for various continuous martingale processes, either with respect to their diffusions coefficients for L\'evy-driven SDEs or their integrands for stochastic integrals. Main results are bordered…

Probability · Mathematics 2014-07-24 Gilles Pagès

We consider the statistical deconvolution problem where one observes $n$ replications from the model $Y=X+\epsilon$, where $X$ is the unobserved random signal of interest and $\epsilon$ is an independent random error with distribution…

Statistics Theory · Mathematics 2011-03-09 Karim Lounici , Richard Nickl

In a recent paper by two of the authors, the concepts of upwards and downwards $\epsilon$-movability were introduced, mainly as a technical tool for studying dynamical percolation of interacting particle systems. In this paper, we further…

Probability · Mathematics 2007-05-23 Erik I. Broman , Olle Haggstrom , Jeffrey E. Steif

We study Fourier multipliers which result from modulating jumps of L\'evy processes. Using the theory of martingale transforms we prove that these operators are bounded in $L^p(\Rd)$ for $1<p<\infty$ and we obtain the same explicit bound…

Functional Analysis · Mathematics 2007-05-23 Rodrigo Bañuelos , Krzysztof Bogdan

In this paper, we establish maximal concentration bounds for the iterates generated by a stochastic approximation (SA) algorithm under a contractive operator with respect to some arbitrary norm (for example, the $\ell_\infty$-norm). We…

Machine Learning · Computer Science 2024-09-18 Zaiwei Chen , Siva Theja Maguluri , Martin Zubeldia