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The DUCK-calculus presented here is a recent approach to cope with probabilistic uncertainty in a sound and efficient way. Uncertain rules with bounds for probabilities and explicit conditional independences can be maintained incrementally.…

Artificial Intelligence · Computer Science 2013-03-25 Helmut Thone , Ulrich Guntzer , Werner Kiessling

We present a derivation and theoretical investigation of the Adams-Bashforth and Adams-Moulton family of linear multistep methods for solving ordinary differential equations, starting from a Gaussian process (GP) framework. In the limit,…

Numerical Analysis · Mathematics 2018-10-10 Onur Teymur , Konstantinos Zygalakis , Ben Calderhead

We study the problem of model selection type aggregation with respect to the Kullback-Leibler divergence for various probabilistic models. Rather than considering a convex combination of the initial estimators $f_1, \ldots, f_N$, our…

Statistics Theory · Mathematics 2016-01-22 Cristina Butucea , Jean-François Delmas , Anne Dutfoy , Richard Fischer

This article provides quasi-optimal a priori error estimates for an optimal control problem constrained by an elliptic obstacle problem where the finite element discretization is carried out using the symmetric interior penalty…

Numerical Analysis · Mathematics 2023-12-21 Harbir Antil , Rohit Khandelwal , Umarkhon Rakhimov

Under typical scaling, the last passage time field of the directed last passage percolation model with exponential site distributions converges to the KPZ fixed point. In this paper, we consider an atypical scenario in which the last…

Probability · Mathematics 2025-08-14 Jinho Baik , Dylan Cordaro , Tejaswi Tripathi

We present global convergence rates for a line-search method which is based on random first-order models and directions whose quality is ensured only with certain probability. We show that in terms of the order of the accuracy, the…

Optimization and Control · Mathematics 2017-01-06 Coralia Cartis , Katya Scheinberg

We study a stochastic optimal control problem for fully coupled forward-backward stochastic control systems with a nonempty control domain. For our problem, the first-order and second-order variational equations are fully coupled linear…

Optimization and Control · Mathematics 2018-12-05 Mingshang Hu , Shaolin Ji , Xiaole Xue

Given a family of probability measures in P(X), the space of probability measures on a Hilbert space X, our goal in this paper is to highlight one ore more curves in P(X) that summarize efficiently that family. We propose to study this…

Machine Learning · Statistics 2015-11-24 Vivien Seguy , Marco Cuturi

We extend the convergence analysis for methods solving PDE-constrained optimal control problems containing both discrete and continuous control decisions based on relaxation and rounding strategies to the class of first order semilinear…

Optimization and Control · Mathematics 2015-09-15 Falk M. Hante

This paper explores an iterative coupling approach to solve linear thermo-poroelasticity problems, with its application as a high-fidelity discretization utilizing finite elements during the training of projection-based reduced order…

Numerical Analysis · Mathematics 2024-01-08 Francesco Ballarin , Sanghyun Lee , Son-Young Yi

For the iterative decoupling of elliptic-parabolic problems such as poroelasticity, we introduce time discretization schemes up to order $5$ based on the backward differentiation formulae. Its analysis combines techniques known from…

Numerical Analysis · Mathematics 2026-05-25 Robert Altmann , Abdullah Mujahid , Benjamin Unger

This monograph resolves - in a dense class of cases - several open problems concerning geodesics in i.i.d. first-passage percolation on $\mathbb{Z}^d$. Our primary interest is in the empirical measures of edge-weights observed along…

Probability · Mathematics 2021-10-04 Erik Bates

We present a new approach to study measures on ensembles of contours, polymers or other objects interacting by some sort of exclusion condition. For concreteness we develop it here for the case of Peierls contours. Unlike existing methods,…

Probability · Mathematics 2016-08-15 Roberto Fernández , Pablo A. Ferrari , Nancy L. Garcia

Variational Optimization forms a differentiable upper bound on an objective. We show that approaches such as Natural Evolution Strategies and Gaussian Perturbation, are special cases of Variational Optimization in which the expectations are…

Machine Learning · Statistics 2018-09-14 Thomas Bird , Julius Kunze , David Barber

The interplay between two-dimensional percolation growth models and one-dimensional particle processes has been a fruitful source of interesting mathematical phenomena. In this paper we develop a connection between the construction of…

Probability · Mathematics 2010-01-26 Eric Cator , Leandro P. R. Pimentel

The thesis concentrates on two problems in discrete geometry, whose solutions are obtained by analytic, probabilistic and combinatoric tools. The first chapter deals with the strong polarization problem. This states that for any sequence…

Metric Geometry · Mathematics 2019-07-12 Gergely Ambrus

We establish the scaling limit of the geodesics to the root for the first passage percolation distance on random planar maps. We first describe the scaling limit of the number of faces along the geodesics. This result enables us to compare…

Probability · Mathematics 2025-09-15 Emmanuel Kammerer

Bi-infinite geodesics are fundamental objects of interest in planar first passage percolation. A longstanding conjecture states that under mild conditions there are almost surely no bigeodesics, however the result has not been proved in any…

Probability · Mathematics 2021-02-09 Riddhipratim Basu , Christopher Hoffman , Allan Sly

We consider geodesically convex optimization problems involving distances to a finite set of points $A$ in a CAT(0) cubical complex. Examples include the minimum enclosing ball problem, the weighted mean and median problems, and the…

Optimization and Control · Mathematics 2024-05-06 Ariel Goodwin , Adrian S. Lewis , Genaro Lopez-Acedo , Adriana Nicolae

Recent developments in extreme value statistics have established the so-called geometric approach as a powerful modelling tool for multivariate extremes. We tailor these methods to the case of spatial modelling and examine their efficacy at…

Methodology · Statistics 2026-02-20 Lydia Kakampakou , Jennifer L. Wadsworth