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We consider a slightly modified form of the standard Rudin-Keisler order on ideals and demonstrate the existence of complete (with respect to this order) ideals in various projective classes. Using our methods, we obtain a simple proof of…

Logic · Mathematics 2014-06-20 Konstantinos A. Beros

While it is well known that the restricted isometry property (RIP) guarantees uniform sparse recovery from noisy linear measurements, uniform recovery of structured signals from nonlinear observations remains much less understood. This…

Information Theory · Computer Science 2026-04-23 Pedro Abdalla , Radu Balan , Junren Chen

The Kruskal Katona theorem was proved in the 1960s. In the theorem, we are given an integer $r$ and families of sets $\mathcal{A}\subset \mathbb{N}^{(r)}$ and $\mathcal{B}\subset\mathbb{N}^{(r-1)}$ such that for every $A\in\mathcal{A}$,…

Combinatorics · Mathematics 2018-05-02 Matthew Fitch

We give elementary proofs of the theorems mentioned in the title. Our methods rely on a simple version of Ramsey theory and a martingale difference lemma. They also provide quantitative results: if a Banach space contains $\ell^{1}$ only…

Functional Analysis · Mathematics 2016-09-06 Ehrhard Behrends

These are the lecture notes of an introductory course on ordinal analysis. Our selection of topics is guided by the aim to give a complete and direct proof of a mathematical independence result: Kruskal's theorem for binary trees is…

Logic · Mathematics 2022-04-22 Anton Freund

We use the repeated averages hierarchy to prove a Ramsey theorem regarding uniform upper estimates of convex block sequences of weakly null sequences. The base case of the theorem recovers a result of Freeman.

Functional Analysis · Mathematics 2020-03-26 R. M. Causey

The principle $ADS$ asserts that every linear order on $\omega$ has an infinite ascending or descending sequence. This has been studied extensively in the reverse mathematics literature, beginning with the work of Hirschfeldt and Shore. We…

Logic · Mathematics 2016-05-23 Eric P. Astor , Damir D. Dzhafarov , Reed Solomon , Jacob Suggs

The well-known Kruskal-Katona theorem in combinatorics says that (under mild conditions) every monotone Boolean function $f: \{0,1\}^n \to \{0,1\}$ has a nontrivial "density increment." This means that the fraction of inputs of Hamming…

Computational Complexity · Computer Science 2019-11-04 Anindya De , Rocco A. Servedio

Lieb and Ruskai's strong subadditivity theorem, which shows that the conditional mutual information must be nonnegative, is fundamental in quantum theory. It has numerous applications, such as in quantum error correction. When the mutual…

Quantum Physics · Physics 2026-05-26 Zhou Gang

We give a robust version of the celebrated result of Kruskal on the uniqueness of tensor decompositions: we prove that given a tensor whose decomposition satisfies a robust form of Kruskal's rank condition, it is possible to approximately…

Data Structures and Algorithms · Computer Science 2013-05-01 Aditya Bhaskara , Moses Charikar , Aravindan Vijayaraghavan

The aim of this paper is to determine the logical and computational strength of instances of the Bolzano-Weierstra{\ss} principle (BW) and a weak variant of it. We show that BW is instance-wise equivalent to the weak K\"onig's lemma for…

Logic · Mathematics 2012-05-08 Alexander P. Kreuzer

We consider identification and inference about a counterfactual outcome mean when there is unmeasured confounding using tools from proximal causal inference (Miao et al. [2018], Tchetgen Tchetgen et al. [2020]). Proximal causal inference…

Methodology · Statistics 2023-10-03 Jeffrey Zhang , Wei Li , Wang Miao , Eric Tchetgen Tchetgen

An important result in discrepancy due to Banaszczyk states that for any set of $n$ vectors in $\mathbb{R}^m$ of $\ell_2$ norm at most $1$ and any convex body $K$ in $\mathbb{R}^m$ of Gaussian measure at least half, there exists a $\pm 1$…

Data Structures and Algorithms · Computer Science 2017-08-04 Nikhil Bansal , Daniel Dadush , Shashwat Garg , Shachar Lovett

The purpose of this article is to study the role of G\"odel's functional interpretation in the extraction of programs from proofs in well quasi-order theory. The main focus is on the interpretation of Nash-Williams' famous minimal bad…

Logic · Mathematics 2017-06-12 Thomas Powell

We prove that the Cohesiveness Principle (COH) is $\Pi^1_1$ conservative over $RCA_0 + I\Sigma^0_n$ and over $RCA_0 + B\Sigma^0_n$ for all $n \geq 2$ by recursion-theoretic means. We first characterize COH over $RCA_0 + B\Sigma^0_2$ as a…

Logic · Mathematics 2022-12-27 David R. Belanger

We give a characterization of the existence of copies of $c_{0}$ in Banach spaces in terms of indexes. As an application, we deduce new proofs of James Distortion theorem and Bessaga-Pe{\l}czynski theorem about weakly unconditionally Cauchy…

Functional Analysis · Mathematics 2016-03-30 A. Pérez , M. Raja

Consider a fixed universe of $N=2^n$ elements and the uniform distribution over elements of some subset of size $K$. Given samples from this distribution, the task of complement sampling is to provide a sample from the complementary subset.…

Quantum Physics · Physics 2026-02-02 Marcello Benedetti , Harry Buhrman , Jordi Weggemans

We consider two theorems from the theory of compressive sensing. Mainly a theorem concerning uniform recovery of random sampling matrices, where the number of samples needed in order to recover an $s$-sparse signal from linear measurements…

Information Theory · Computer Science 2013-06-05 Joel Andersson , Jan-Olov Strömberg

In the present paper, we study extreme negative dependence focussing on the concordance order for copulas. With the absence of a least element for dimensions $d\ge$ 3, the set of all minimal elements in the collection of all copulas turns…

Statistics Theory · Mathematics 2018-10-22 Jae Youn Ahn , Sebastian Fuchs

Contrastive learning is a powerful framework for learning self-supervised representations that generalize well to downstream supervised tasks. We show that multiple existing contrastive learning methods can be reinterpreted as learning…

Machine Learning · Computer Science 2023-02-16 Daniel D. Johnson , Ayoub El Hanchi , Chris J. Maddison