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The theory of majorizing measures, extensively developed by Fernique, Talagrand and many others, provides one of the most general frameworks for controlling the behavior of stochastic processes. In particular, it can be applied to derive…

Probability · Mathematics 2020-12-25 Sander Borst , Daniel Dadush , Neil Olver , Makrand Sinha

We derive two-sided bounds for expected values of suprema of canonical processes based on random variables with moments growing regularly. We also discuss a Sudakov-type minoration principle for canonical processes.

Probability · Mathematics 2016-04-05 Rafał Latała , Tomasz Tkocz

The majorizing measure theorem of Fernique and Talagrand is a fundamental result in the theory of random processes. It relates the boundedness of random processes indexed by elements of a metric space to complexity measures arising from…

Information Theory · Computer Science 2023-05-09 Yifeng Chu , Maxim Raginsky

In this paper we give an ordinal analysis of the theory of second order arithmetic. We do this by working with proof trees -- that is, "deductions" which may not be well-founded. Working in a suitable theory, we are able to represent…

Logic · Mathematics 2024-03-27 Henry Towsner

The first step to study lower bounds for a stochastic process is to prove a special property - Sudakov minoration. The property means that if a certain number of points from the index set are well separated then we can provide an optimal…

Probability · Mathematics 2022-09-20 Witold Bednorz

We introduce a random probability measure on the profinite completion of the random tree of a branching process and introduce the canonical and grand canonical ensembles of random repelling particles on this random profinite completion at…

Mathematical Physics · Physics 2024-07-10 Christopher D. Sinclair

We present three methods to construct majorizing measures in various settings. These methods are based on direct constructions of increasing sequences of partitions through a simple exhaustion procedure rather than on the construction of…

Functional Analysis · Mathematics 2009-09-25 Michel Talagrand

This paper presents a canonical d.c. (difference of canonical and convex functions) programming problem, which can be used to model general global optimization problems in complex systems. It shows that by using the canonical duality…

Optimization and Control · Mathematics 2016-07-13 Zhong Jin , David Y Gao

This paper presents a canonical duality theory for solving a general nonconvex constrained optimization problem within a unified framework to cover Lagrange multiplier method and KKT theory. It is proved that if both target function and…

Optimization and Control · Mathematics 2013-10-09 Vittorio Latorre , David Y. Gao

We discuss the method of bounding suprema of canonical processes based on the inclusion of their index set into a convex hull of a well-controlled set of points. While the upper bound is immediate, the reverse estimate was established to…

Probability · Mathematics 2024-05-24 Rafał Latała

The canonical duality theory has provided with a unified analytic solution to a range of discrete and continuous problems in global optimization, which can transform a nonconvex primal problem to a concave maximization dual problem over a…

Optimization and Control · Mathematics 2012-10-04 Xiaojun Zhou

For fixed $t\ge 2$, we consider the class of representations of $1$ as sum of unit fractions whose denominators are powers of $t$ or equivalently the class of canonical compact $t$-ary Huffman codes or equivalently rooted $t$-ary plane…

Number Theory · Mathematics 2015-09-16 Clemens Heuberger , Daniel Krenn , Stephan Wagner

This paper presents a canonical dual approach for solving a nonlinear population growth problem governed by the well-known logistic equation. Using the finite difference and least squares methods, the nonlinear differential equation is…

Chaotic Dynamics · Physics 2012-06-13 Ning Ruan , David Y. Gao

The expected supremum of a Gaussian process indexed by the image of an index set under a function class is bounded in terms of separate properties of the index set and the function class. The bound is relevant to the estimation of nonlinear…

Machine Learning · Computer Science 2014-11-12 Andreas Maurer

A unified model is addressed for general optimization problems in multi-scale complex systems. Based on necessary conditions and basic principles in physics, the canonical duality-triality theory is presented in a precise way to include…

Optimization and Control · Mathematics 2016-06-30 David Yang Gao

In this paper linear canonical correlation analysis (LCCA) is generalized by applying a structured transform to the joint probability distribution of the considered pair of random vectors, i.e., a transformation of the joint probability…

Methodology · Statistics 2015-06-03 Koby Todros , Alfred O. Hero

In this article we prove that for any orthonormal system $(\vphi_j)_{j=1}^n \subset L_2$ that is bounded in $L_{\infty}$, and any $1 < k <n$, there exists a subset $I$ of cardinality greater than $n-k$ such that on $\spa\{\vphi_i\}_{i \in…

Functional Analysis · Mathematics 2008-01-24 Olivier Guedon , Shahar Mendelson , Alain Pajor , Nicole Tomczak-Jaegermann

This work introduces a canonical structure for a broad class of unconstrained first-order algorithms that admit a Lur'e representation, including systems with relative degree greater than one, e.g., systems with delayed gradient feedback.…

Optimization and Control · Mathematics 2026-04-06 Mengmou Li , Yu Zhou , Xun Shen , Masaaki Nagahara

We look for partition theorems for large subtrees for suitable uncountable trees and colourings. We concentrate on sub-trees of $^{\kappa \ge} 2$ expanded by a well ordering of each level. Unlike earlier works, we do not ask the embedding…

Logic · Mathematics 2026-01-06 Saharon Shelah

Algorithmic meta-theorems state that problems definable in a fixed logic can be solved efficiently on structures with certain properties. An example is Courcelle's Theorem, which states that all problems expressible in monadic second-order…

Logic in Computer Science · Computer Science 2025-01-09 Max Bannach , Markus Hecher
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