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Clustering under pairwise constraints is an important knowledge discovery tool that enables the learning of appropriate kernels or distance metrics to improve clustering performance. These pairwise constraints, which come in the form of…

Machine Learning · Computer Science 2022-03-24 Benedikt Boecking , Vincent Jeanselme , Artur Dubrawski

Long-distance quantum communication via entanglement distribution is of great importance for the quantum internet. However, scaling up to such long distances has proved challenging due to the loss of photons, which grows exponentially with…

An embedded selective recoupling method is proposed which is based on the idea of embedding the recently proposed deterministic selective recoupling scheme of Yamaguchi et al. [quant-ph/0411099] into a stochastic dynamical decoupling…

Quantum Physics · Physics 2007-05-23 O. Kern , G. Alber

Coupling-based normalizing flows (e.g. RealNVP) are a popular family of normalizing flow architectures that work surprisingly well in practice. This calls for theoretical understanding. Existing work shows that such flows weakly converge to…

Machine Learning · Computer Science 2022-10-26 Felix Draxler , Christoph Schnörr , Ullrich Köthe

We consider an $n$-tuple of independent ergodic Markov processes, each of which converges (in the sense of separation distance) at an exponential rate, and obtain a necessary and sufficient condition for the $n$-tuple to exhibit a…

Probability · Mathematics 2010-03-19 Stephen B. Connor

The inverse scattering problem from the multi-frequency backscattering data is a long-standing open problem. We advance the theory by proving a local uniqueness result. Moreover, we introduce a direct sampling method for quantitatively…

Numerical Analysis · Mathematics 2026-04-29 Yukun Guo , Xiaodong Liu

We introduce a reversible Markovian coagulation-fragmentation process on the set of partitions of $\{1,\ldots,L\}$ into disjoint intervals. Each interval can either split or merge with one of its two neighbors. The invariant measure can be…

Probability · Mathematics 2013-11-27 Cedric Bernardin , Fabio Lucio Toninelli

We explore the applications of our previously established likelihood-ratio method for deriving concentration inequalities for a wide variety of univariate and multivariate distributions. New concentration inequalities for various…

Statistics Theory · Mathematics 2014-09-23 Xinjia Chen

Large momentum effective theory allows extraction of hadron parton distribution functions in lattice QCD by matching them to quark bilinear matrix elements of hadrons with large momenta. We calculate the matching kernels for the…

High Energy Physics - Lattice · Physics 2022-08-17 Chien-Yu Chou , Jiunn-Wei Chen

The paper illustrates an application of the Resampling approach [2] for the estimation of the aircraft circulation plan reliability. Resampling is an intensive computer statistical method, which can be used effectively in the case of small…

Applications · Statistics 2013-05-14 Maxim Fioshin

We introduce quantum versions of the $\chi^2$-divergence, provide a detailed analysis of their properties, and apply them in the investigation of mixing times of quantum Markov processes. An approach similar to the one presented in [1-3]…

Quantum Physics · Physics 2024-04-08 K. Temme , M. J. Kastoryano , M. B. Ruskai , M. M. Wolf , F. Verstraete

Gradient schemes is a framework which enables the unified convergence analysis of many different methods -- such as finite elements (conforming, non-conforming and mixed) and finite volumes methods -- for $2^{\rm nd}$ order diffusion…

Numerical Analysis · Mathematics 2018-10-09 Yahya Alnashri , Jerome Droniou

We consider a class of sampling-based decomposition methods to solve risk-averse multistage stochastic convex programs. We prove a formula for the computation of the cuts necessary to build the outer linearizations of the recourse…

Optimization and Control · Mathematics 2016-09-12 Vincent Guigues

We propose an approximation scheme for a class of semilinear variational inequalities whose Hamiltonian is convex and coercive. The proposed scheme is a natural extension of a previous splitting scheme proposed by Liang, Zariphopoulou and…

Numerical Analysis · Mathematics 2019-11-05 Shuo Huang

Observing that the recent developments of the recursive (product) quantization method induces a family of Markov chains which includes all standard discretization schemes of diffusions processes , we propose to compute a general error bound…

Probability · Mathematics 2018-08-30 Gilles Pagès , Abass Sagna

We analyze the convergence of piecewise collocation methods for computing periodic solutions of general retarded functional differential equations under the abstract framework recently developed in [S. Maset, Numer. Math. (2016)…

Numerical Analysis · Mathematics 2020-12-02 Alessia Andò , Dimitri Breda

A multi-type branching process is defined as a random tree with labeled vertices, where each vertex produces offspring independently according to the same multivariate probability distribution. We demonstrate that in realizations of the…

Probability · Mathematics 2025-03-31 Jochem Hoogendijk , Ivan Kryven , Rik Versendaal

This paper demonstrates a new regeneration processes technology making use of positive stable distributions. We study the asymptotic behavior of branching processes with a randomly controlled migration component. Using the new method, we…

Probability · Mathematics 2007-05-23 George P. Yanev , Kosto V. Mitov , Nickolay M. Yanev

Quantum entanglement is an indispensable resource for many significant quantum information processing tasks. However, because of the noise in quantum channels, it is difficult to distribute quantum entanglement over a long distance in…

Quantum Physics · Physics 2018-01-31 Zhaofeng Su , Ji Guan , Lvzhou Li

We consider a general preferential attachment model, where the probability that a newly arriving vertex connects to an older vertex is proportional to a sublinear function of the indegree of the older vertex at that time. It is well known…

Probability · Mathematics 2018-05-04 Carina Betken , Hanna Döring , Marcel Ortgiese