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Related papers: Sharp rate for the dual quantization problem

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We develop a new approach to vector quantization, which guarantees an intrinsic stationarity property that also holds, in contrast to regular quantization, for non-optimal quantization grids. This goal is achieved by replacing the usual…

Probability · Mathematics 2013-04-05 Gilles Pagès , Benedikt Wilbertz

We establish a Zador like theorem for $L^r$-optimal vector quantization when the similarity measure is a twice differentiable Bregman divergence of a strictly convex function. On our way we also prove a similar result when the Bregman…

Functional Analysis · Mathematics 2026-04-06 Guillaume Boutoille , Gilles Pagès

Zador's celebrated theorem is a cornerstone of optimal quantisation, establishing both the weak limit of the empirical distribution of an $n$-point optimal quantiser in $R^d$ and the decay rate of the associated $L_s$-mean quantisation…

Statistics Theory · Mathematics 2026-05-14 Luc Pronzato , Anatoly Zhigljavsky

The problem of quantization of measures looks for best approximations of probability measures on a metric space by discrete measures supported on $N$ points, where the error of approximation is measured with respect to the Wasserstein…

Metric Geometry · Mathematics 2026-02-17 Ata Deniz Aydin

We observe $(X_i,Y_i)_{i=1}^n$ where the $Y_i$'s are real valued outputs and the $X_i$'s are $m\times T$ matrices. We observe a new entry $X$ and we want to predict the output $Y$ associated with it. We focus on the high-dimensional…

Statistics Theory · Mathematics 2010-09-01 Stéphane Gaïffas , Guillaume Lecué

We establish for dual quantization the counterpart of Kieffer's uniqueness result for compactly supported one dimensional probability distributions having a $\log$-concave density (also called strongly unimodal): for such distributions,…

Probability · Mathematics 2020-10-22 Benjamin Jourdain , Gilles Pagès

Deep neural networks have achieved state-of-the-art results in a wide range of applications, from natural language processing and computer vision to speech recognition. However, as tasks become increasingly complex, model sizes continue to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Tomer Gafni , Asaf Karnieli , Yair Hanani

In the present paper, we consider the Cauchy problem of the system of quadratic derivative nonlinear Schr\"odinger equations for the spatial dimension $d=2$ and $3$. This system was introduced by M. Colin and T. Colin (2004). The first…

Analysis of PDEs · Mathematics 2024-09-12 Hiroyuki Hirayama , Shinya Kinoshita

Sup-norm curve estimation is a fundamental statistical problem and, in principle, a premise for the construction of confidence bands for infinite-dimensional parameters. In a Bayesian framework, the issue of whether the…

Methodology · Statistics 2016-03-22 Catia Scricciolo

We give a self-contained proof of the $A_2$ conjecture, which claims that the norm of any Calderon-Zygmund operator is bounded by the first degree of the $A_2$ norm of the weight. The original proof of this result by the first author relied…

Classical Analysis and ODEs · Mathematics 2010-12-09 Tuomas Hytönen , Carlos Pérez , Sergei Treil , Alexander Volberg

We describe algorithms which address two classical problems in lattice geometry: the lattice covering and the simultaneous lattice packing-covering problem. Theoretically our algorithms solve the two problems in any fixed dimension d in the…

Metric Geometry · Mathematics 2007-05-23 Achill Schuermann , Frank Vallentin

An extension of the restricted Delaunay-refinement algorithm for surface mesh generation is described, where a new point-placement scheme is introduced to improve element quality in the presence of mesh size constraints. Specifically, it is…

Computational Geometry · Computer Science 2016-06-28 Darren Engwirda , David Ivers

Two-sample hypothesis testing is a fundamental problem with various applications, which faces new challenges in the high-dimensional context. To mitigate the issue of the curse of dimensionality, high-dimensional data are typically assumed…

Methodology · Statistics 2026-04-06 Jiaqi Gu , Ruoxu Tan , Guosheng Yin

A new version of the modified theory of gravity is formulated in which two physical metrics are constructed out of two vierbeins connected with each other by the duality condition including the flat metric of the prior geometry. The duality…

General Relativity and Quantum Cosmology · Physics 2025-05-20 V. I. Tselyaev

In this work, we summarize the linearization method to study the Heisenberg Uncertainty Principles, and explain that the same approach can be used to handle the stability problem. As examples of application, combining with spherical…

Analysis of PDEs · Mathematics 2025-10-02 Xia Huang , Dong Ye

There is a recent interest on first-order methods for linear programming (LP). In this paper,we propose a stochastic algorithm using variance reduction and restarts for solving sharp primal-dual problems such as LP. We show that the…

Optimization and Control · Mathematics 2024-01-02 Haihao Lu , Jinwen Yang

This paper is concerned with Darcy's law for an incompressible viscous fluid flowing in a porous medium. We establish the sharp $O(\sqrt{\e})$ convergence rate in a periodically perforated and bounded domain in $R^d$ for $d\ge 2$, where…

Analysis of PDEs · Mathematics 2022-01-28 Zhongwei Shen

We develop the theory of strong stationary duality for diffusion processes on compact intervals. We analytically derive the generator and boundary behavior of the dual process and recover a central tenet of the classical Markov chain theory…

Probability · Mathematics 2015-04-20 James Allen Fill , Vince Lyzinski

The central topic of this thesis is two dimensional Quantum Gravity and its properties. The term Quantum Gravity itself is ambiguous as there are many proposals for its correct formulation and none of them have been verified experimentally.…

High Energy Physics - Theory · Physics 2011-12-01 Max R. Atkin

Both complete decoupling and tangent decoupling are classical tools aiming to compare two random processes where one has a weaker dependence structure. We give a new proof for the complete decoupling inequality, which provides a lower bound…

Probability · Mathematics 2025-12-23 Victor H. de la Pena , Heyuan Yao , Demissie Alemayehu
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