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We prove that Higman's lemma is strictly stronger for better quasi orders than for well quasi orders, within the framework of reverse mathematics. In fact, we show a stronger result: the infinite Ramsey theorem (for tuples of all lengths)…

Logic · Mathematics 2022-05-10 Anton Freund

Let $S= \{ p_1, \ldots, p_s\}$ be a finite, non-empty set of distinct prime numbers and $(U_{n})_{n \geq 0}$ be a linear recurrence sequence of integers of order $r$. For any positive integer $k,$ we define $(U_j^{(k)})_{j\geq 1}$ an…

Number Theory · Mathematics 2020-04-16 S. S. Rout , N. K. Meher

We show a short proof of Higman's lemma using Friedman's adjacent Ramsey theorem for pairs. This provides an alternative proof of the known upper bound for the reverse mathematical status of Higman's lemma and that of its miniaturised…

Logic · Mathematics 2016-03-01 Florian Pelupessy

We derive upper bounds on the complexity of ReLU neural networks approximating the solution of a linear system given the matrix and the right-hand side. We focus on matrices which are symmetric positive definite and sparse, as they appear…

Numerical Analysis · Mathematics 2026-03-20 Benjamin Dörich , Roland Maier , Lukas Ullmer

We introduce new combinatorial quantities for concept classes, and prove lower and upper bounds for learning complexity in several models of query learning in terms of various combinatorial quantities. Our approach is flexible and powerful…

Machine Learning · Computer Science 2019-04-24 Hunter Chase , James Freitag

Finding tight bounds on the optimal solution is a critical element of practical solution methods for discrete optimization problems. In the last decade, decision diagrams (DDs) have brought a new perspective on obtaining upper and lower…

Artificial Intelligence · Computer Science 2019-02-28 Quentin Cappart , Emmanuel Goutierre , David Bergman , Louis-Martin Rousseau

Sequence representations supporting queries $access$, $select$ and $rank$ are at the core of many data structures. There is a considerable gap between the various upper bounds and the few lower bounds known for such representations, and how…

Data Structures and Algorithms · Computer Science 2013-08-26 Djamal Belazzougui , Gonzalo Navarro

We consider the problem of identifying the parameters of an unknown mixture of two arbitrary $d$-dimensional gaussians from a sequence of independent random samples. Our main results are upper and lower bounds giving a computationally…

Machine Learning · Computer Science 2015-05-19 Moritz Hardt , Eric Price

We investigate strong divisibility sequences and produce lower and upper bounds for the density of integers in the sequence which only have (somewhat) large prime factors. We focus on the special cases of Fibonacci numbers and elliptic…

Number Theory · Mathematics 2025-09-03 Tim Browning , Matteo Verzobio

Nakano's "later" modality, inspired by G\"{o}del-L\"{o}b provability logic, has been applied in type systems and program logics to capture guarded recursion. Birkedal et al modelled this modality via the internal logic of the topos of…

Logic in Computer Science · Computer Science 2015-04-20 Ranald Clouston , Rajeev Goré

Systems of decision rules and decision trees are widely used as a means for knowledge representation, as classifiers, and as algorithms. They are among the most interpretable models for classifying and representing knowledge. The study of…

Computational Complexity · Computer Science 2023-02-15 Kerven Durdymyradov , Mikhail Moshkov

This paper illustrates the richness of the concept of regular sets of time bounds and demonstrates its application to problems of computational complexity. There is a universe of bounds whose regular subsets allow to represent several time…

Computational Complexity · Computer Science 2013-09-24 Armin Hemmerling

A typical way of analyzing the time complexity of functional programs is to extract a recurrence expressing the running time of the program in terms of the size of its input, and then to solve the recurrence to obtain a big-O bound. For…

Programming Languages · Computer Science 2020-08-03 Joseph W. Cutler , Daniel R. Licata , Norman Danner

The reflection principle is the statement that if a sentence is provable then it is true. Reflection principles have been studied for first-order theories, but they also play an important role in propositional proof complexity. In this…

Logic · Mathematics 2020-07-30 Pavel Pudlák

We improve lower bounds on the $k$th-order nonlinear complexity of pseudorandom sequences over finite fields and we establish a probabilistic result on the behavior of the $k$th-order nonlinear complexity of random sequences over finite…

Information Theory · Computer Science 2013-12-06 Harald Niederreiter , Chaoping Xing

Upper bound limit analysis allows one to evaluate directly the ultimate load of structures without performing a cumbersome incremental analysis. In order to numerically apply this method to thin plates in bending, several authors have…

Numerical Analysis · Mathematics 2014-10-02 Jérémy Bleyer , Guillaume Carlier , Vincent Duval , Jean-Marie Mirebeau , Gabriel Peyré

We consider the problem of sequential prediction and provide tools to study the minimax value of the associated game. Classical statistical learning theory provides several useful complexity measures to study learning with i.i.d. data. Our…

Machine Learning · Computer Science 2014-08-13 Alexander Rakhlin , Karthik Sridharan , Ambuj Tewari

Termination is a major question in both logic and computer science. In logic, termination is at the heart of proof theory where it is usually called strong normalization (of cut elimination). In computer science, termination has always been…

Logic in Computer Science · Computer Science 2016-08-16 Frédéric Blanqui , Jean-Pierre Jouannaud , Albert Rubio

Classical complexity theory measures the cost of computing a function, but many computational tasks require committing to one valid output among several. We introduce determination depth -- the minimum number of sequential layers of…

Computational Complexity · Computer Science 2026-04-08 Joseph M. Hellerstein

We show that unlike machine learning classifiers, there are no complex boundary structures in the decision boundaries for well-trained deep models. However, we found that the complicated structures do appear in training but they vanish…

Machine Learning · Computer Science 2022-11-30 Hengshuai Yao
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